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1
Yao, Christian, Modeste Kacou, Ehouman Serge Koffi, Amidou Dao, Clément Dutremble, Maurice Guilliod, Bamory Kamagaté, et al. "Rainfall risk over the city of Abidjan (Côte d'Ivoire): first contribution of the joint analysis of daily rainfall from a historical record and a recent network of rain gauges." Proceedings of IAHS 385 (April 18, 2024): 259–65. http://dx.doi.org/10.5194/piahs-385-259-2024.
Повний текст джерелаАнотація:
Abstract. Every year, rains cause material damage and human losses, in Abidjan (Côte d'Ivoire). The objective of this study is to contribute to the characterization of the rain hazard in the District of Abidjan. The available data are made up of daily rainfall from a historical station “Abidjan airport” (1961–2014) and an academic network of rain gauges (21) progressively implemented in Abidjan since 2015. A descriptive analysis (date of occurrence, rainfall depth, mean wet days intensity and number of rainy days) on the Highest Cumulative Rainfall Periods (HCRP: 60 d) is conducted on the long-term station. The periods of highest risk of flooding during the long and short rainy seasons are characterized. The Experimental variograms of extreme rainfalls derived from the current network, allow to evaluate their extensions according to the rainy season.
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Palharini, Rayana, Daniel Vila, Daniele Rodrigues, Rodrigo Palharini, Enrique Mattos, and Eduardo Undurraga. "Analysis of Extreme Rainfall and Natural Disasters Events Using Satellite Precipitation Products in Different Regions of Brazil." Atmosphere 13, no. 10 (October 14, 2022): 1680. http://dx.doi.org/10.3390/atmos13101680.
Повний текст джерелаАнотація:
The number of natural disasters triggered by extreme events is increasing worldwide and significantly impacts modern society. Extreme rainfall is one of the most important factors contributing to these events. A better understanding of the physical process that causes extreme rainfall can allow rapid responses from decision-makers to lessen the impact of natural disasters on the local population. Satellite monitoring is widely used for this purpose and is essential for regions where terrestrial observations are limited or non-existent. The primary purpose of this study is to describe the performance of satellite products for extreme rainfall events that caused natural disasters in various climate regimes in Brazil and discuss the contribution of mesoscale convective systems (MCS) to these events. We defined regions based on the climatological rainfall distribution. Cases with rain values above the 99th percentile during 2012–2016 were considered statistically extreme. Our analysis is based on three datasets, with precipitation from (i) rain gauge stations, (ii) different satellite-based estimates, and (iii) mesoscale convective tracking data. The methodology was based on identifying extreme rainfall events, analyzing the performance of satellite precipitation estimates and, finally, quantifying the influence of convective systems on extreme rain. Although all regions of Brazil may be affected by natural disasters caused by extreme rains, the results suggest that the impacts caused in each region are different in magnitude. Convective systems explained over 90% of extreme rains in the case analyzed in Brazil’s south and about 60% to 90% of extreme rains in the case analyzed in the Northeast. In general, satellite products have identified rain events; however, in the southern region of Brazil, products have tended to overestimate rainfall, while other regions have tended to underestimate extreme rain values. The methods used in satellite precipitation estimation products have limitations to accurately identifying specific extreme rain events.
3
Hidayati, Nurul, SB Soeryamassoeka, and Henny Herawati. "RAINFALL ANALYSIS FOR CREATING INTENSITY-DURATION-FREQUENCY (IDF) CURVE OF PONTIANAK CITY." Jurnal Teknik Sipil 23, no. 4 (November 28, 2023): 10. http://dx.doi.org/10.26418/jts.v23i4.66810.
Повний текст джерелаАнотація:
Pontianak is a lowland area prone to flooding if it rains with high rainfall intensity. Analysis of the planned flood discharge is needed to overcome the flood problem. The design flood discharge analysis can be calculated using the rational method, which requires rain intensity data in terms of duration and frequency, which can be described as an IDF curve.This research was conducted by calculating the average daily maximum rainfall after conducting consistency and homogeneity tests on the rainfall data used and determining the selected distribution based on the results of statistical parameters. The rain design with various return periods is calculated with the desired distribution that matches Pontianak City. The rainfall intensity calculation uses the Mononobe method because the rainfall data owned is daily rainfall data.The analysis results show that the Log Pearson Type III distribution corresponds to the data distribution in Pontianak. From the IDF curve, it can be seen that high rainfall intensity lasts for a short duration; this can prove the general nature of rain that the faster the rain stays, the higher the rainfall intensity and vice versa. The IDF curve can assist in calculating the design flood discharge.
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Kim, Min-Seong, and Byung Kwon. "Rainfall Detection and Rainfall Rate Estimation Using Microwave Attenuation." Atmosphere 9, no. 8 (July 24, 2018): 287. http://dx.doi.org/10.3390/atmos9080287.
Повний текст джерелаАнотація:
Eight microwave links operating at frequencies ranging from 6 to 8 GHz and with path lengths ranging from 5.7 to 37.4 km traversing the city of Seoul, Korea are used to detect rainfall and estimate path-averaged rainfall rates. Rainfall detection using rain-induced attenuation (dB) was validated by rain detectors installed at automatic weather stations, and the results confirmed that microwave links can be used to detect rainfall with an accuracy ≥80%. The power-law R-k relationships between rain-induced specific attenuation, k (dB km−1), and the rainfall rate, R (mm h−1), were established and cross-validated by estimating the path-averaged rainfall rate. The mean bias of the path-averaged rainfall rate, as compared to the rainfall rate from ground rain gauges, was between −3 and 1 mm h−1. The improved accuracy of rainfall detection led to the improved accuracy of the path-averaged rainfall rate. Hence, it was confirmed that microwave links, used for broadcasting and media communications, can identify rainy or dry periods (rain spells or dry spells) in a way comparable to rain detectors and provide high time-resolution rainfall rates in real time.
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Subiyanti, Hesti, Ahmad Rifa’i, and Rachmad Jayadi. "Analisis Kelongsoran Lereng Akibat Pengaruh Tekanan Air Pori di Saluran Induk Kalibawang Kulonprogo." Semesta Teknika 14, no. 1 (December 16, 2015): 15–25. http://dx.doi.org/10.18196/st.v14i1.566.
Повний текст джерелаАнотація:
During rainy seasons, landslide occurs every year in Talang Bawong, Kalibawang Irrigation Channel thatcan damage houses, school building, bridge and the channel. Considering this fact, a numerical analysis by modeling the slope at the site was conducted. The objectives of this research were to identify the rain characteristic in the research site and to recognize its influence towards the change of water pressure in soil as well as the slope failure. The input data of this analysis were slope topography, physical and mechanical properties of soil applied. Groundwater flow in the slope model was numerically simulated by using SEEP/W software. Designed rainfall with appropriate return period was determined by analizing the maximum daily rainfall data with the aid of HAVARA software, while rainfall depth distribution was completed by applying frequency analysis. The historical daily rainfall data (1985 – 2004) were obtained from Kalibawang rain stasiun. Six rainfall models, as follow: initial condition (no rain) (model I), heavy rain in a short duration (model II), normal rain 25 mm and 40 mm in a long duration (model III), normal rain 20 mm in a long duration (model IV), heavy rain followed by normal rain 20 mm (model V), and normal rain 20 mm followed by heavy rain (model VI) Were analyzed. The output of the simulation was water pressure distribution data, which in turn being used as input data in analyzing slope stability using the SLOPE/W software. The result of the research showed that the highest rainfall with 2-year-return period was 114 mm while the dominant duration was 4 hours/day, and it was applied in the model II. The result showed that, a normal rain in a long duration is more severely influenced the change in water pressure than a heavy rain in a short duration. The safety factors are 1,444 for no rain condition, 1,418 for 114 mm rain for 4 hours, 1,208 for 25 mm and 40 mm rains, 0,982 for 20 mm rain, 1,397 for heavy rain followed by normal rain, and 1,402 for normal rain followed by heavy rain. In addition, a 20 mm normal rain on the 61st day resulted in the most severe influence on the slope failure.
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Peleg, N., M. Ben-Asher, and E. Morin. "Radar subpixel-scale rainfall variability and uncertainty: a lesson learned from observations of a dense rain-gauge network." Hydrology and Earth System Sciences Discussions 10, no. 1 (January 2, 2013): 1–32. http://dx.doi.org/10.5194/hessd-10-1-2013.
Повний текст джерелаАнотація:
Abstract. Hydrological models for runoff estimations and flash-flood predictions are very sensitive to rainfall's spatial and temporal variability. The increasing use of radar and satellite data in hydrological applications, due to the sparse distribution of rain gauges over most catchments worldwide, requires improving our knowledge of the uncertainties of these data. In 2011, a new super-dense network of rain gauges, containing 27 gauges covering an area of about 4 km2, was installed near Kibbutz Galed in northern Israel. This network was established for a detailed exploration of the uncertainties and errors regarding rainfall variability in remote-sensing at subpixel-scale resolution. In this paper, we present the analysis of the first year's record collected from this network and from the Shacham weather radar. The gauge–rainfall spatial correlation and uncertainty were examined along with the estimated radar error. The zero-distance correlation between rain gauges was high (0.92 on the 1-min scale) and increased as the time scale increased. The variance of the differences between radar pixel rainfall and averaged point rainfall (the variance reduction factor – VRF) was 1.6%, as measured for the 1-min scale. It was also found that at least four uniformly distributed rain stations are needed to represent the rainfall on the radar pixel scale. The radar–rain gauge error was mainly derived from radar estimation errors as the gauge sampling error contributed up to 22% to the total error. The radar rainfall estimations improved with increasing time scale and the radar-to-true rainfall ratio decreased with increasing time scale. Rainfall measurements collected with this network of rain gauges in the coming years will be used for further examination of rainfall's spatial and temporal variability.
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Fernández-Alvarez, José C., Albenis Pérez-Alarcon, Alfo J. Batista-Leyva, and Oscar Díaz-Rodríguez. "Evaluation of Precipitation Forecast of System: Numerical Tools for Hurricane Forecast." Advances in Meteorology 2020 (August 5, 2020): 1–16. http://dx.doi.org/10.1155/2020/8815949.
Повний текст джерелаАнотація:
Heavy rainfall events, typically associated with tropical cyclones (TCs), provoke intense flooding, consequently causing severe losses to life and property. Therefore, the amount and distribution of rain associated with TCs must be forecasted precisely within a reasonable time to guarantee the protection of lives and goods. In this study, the skill of the Numerical Tool for Hurricane Forecast (NTHF) for determining rainfall pattern, average rainfall, rainfall volume, and extreme amounts of rain observed during TCs is evaluated against Tropical Rainfall Measuring Mission (TRMM) data. A sample comprising nine systems formed in the North Atlantic basin from 2016 to 2018 is used, where the analysis begins 24 h before landfall. Several statistical indices characterising the abilities of the NTHF and climatology and persistence model for rainfalls (R-CLIPER) for forecasting rain as measured by the TRMM are calculated at 24, 48, and 72 h forecasts for each TC and averaged. The model under consideration presents better forecasting skills than the R-CLIPER for all the attributes evaluated and demonstrates similar performances compared with models reported in the literature. The proposed model predicts the average rainfall well and presents a good description of the rain pattern. However, its forecast of extreme rain is only applicable for 24 h.
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Hartono, Hartono, Farzand Abdullatif, Sugito Sugito, and Zaroh Irayani. "Design of Turbine-Based Rain Measurement System." Jurnal Teras Fisika 1, no. 1 (February 13, 2018): 34. http://dx.doi.org/10.20884/1.jtf.2018.1.1.359.
Повний текст джерелаАнотація:
Rain measurement systems have significantly developed. In this work, a novel modification to commonly used rain measurement systems is developed. It comprises a turbine with an infrared sensor to detect its rotation. The design of the rainfall collecting funnel refers to that of general use. The prototype of the design has been characterized with an artificial rainfall, namely continuously flowing water kept at a certain debit. For characterization purpose, the water debit is gradually changed to simulate variations in rainfalls. Important results based on the characterization are threshold value of 0.01 mm/min and average deviation of 1.36%, suggesting that this tool is able to detect even a weak rainfall.
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Bridger, Nguyen, and Chiao. "Developing Spatially Accurate Rainfall Predictions for the San Francisco Bay Area through Case Studies of Atmospheric River and other Synoptic Events." Atmosphere 10, no. 9 (September 12, 2019): 541. http://dx.doi.org/10.3390/atmos10090541.
Повний текст джерелаАнотація:
Rainfall patterns in the San Francisco Bay Area (SFBA) are highly influenced by local topography. It has been a forecasting challenge for the main US forecast models. This study investigates the ability of the Weather Research and Forecasting (WRF) model to improve upon forecasts, with particular emphasis on the rain shadow common to the southern end of the SFBA. Three rain events were evaluated: a mid-season atmospheric river (AR) event with copious rains; a typical non-AR frontal passage rain event; and an area-wide rain event in which zero rain was recorded in the southern SFBA. The results show that, with suitable choices of parameterizations, the WRF model with a resolution around 1 km can forecast the observed rainfall patterns with good accuracy, and would be suitable for operational use, especially to water and emergency managers. Additionally, the three synoptic situations were investigated for further insight into the common ingredients for either flooding rains or strong rain shadow events.
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Barszcz, Mariusz Paweł. "Ocena przydatności disdrometru laserowego i radaru meteorologicznego do szacowania wielkości opadów deszczu = Assessment of the suitability of the laser disdrometer and meteorological radar for rainfall estimation." Przegląd Geograficzny 94, no. 4 (2022): 451–70. http://dx.doi.org/10.7163/przg.2022.4.3.
Повний текст джерелаАнотація:
Measurements of precipitation conducted at the WULS-SGGW meteorological station in Warsaw in 2012-2014 and 2019-2020 using a tipping-bucket rain gauge and the laser disdrometer (Parsivel) as well as data obtained from the meteorological radar allowed to collect data enabling the assessment of the usefulness of the disdrometer and radar for estimating rainfalls. The data for the entire study period were used for analysis the correlation relationship between the 24-hour rainfall depths estimated on the basis of the rain gauge and the disdrometer. From the data set for the years 2012-2014, 21 individual events were selected for further analysis, for which rainfall data estimated on the basis of radar in the form of a PAC hydrological product were also available. The rainfall data from the disdrometer and radar were used for analysis the correlation relationships between them and corresponding measurements from the rain gauge. The scope of the study also included a comparison of the values of rainfall totals estimated for 21 single events using the disdrometer and radar in relation to data measured with the rain gauge. The simple method of adjusting the depths of rainfall estimated on the basis of the disdrometer proposed in this paper, was able to reduce significantly the differences in the values of rainfall totals for single events between the data from the disdrometer and the rain gauge.
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Naves, Juan, Jose Anta, Joaquín Suárez, and Jerónimo Puertas. "Development and Calibration of a New Dripper-Based Rainfall Simulator for Large-Scale Sediment Wash-Off Studies." Water 12, no. 1 (January 4, 2020): 152. http://dx.doi.org/10.3390/w12010152.
Повний текст джерелаАнотація:
Rainfall simulators are useful tools for controlling the main variables that govern natural rainfall. In this study, a new drop-forming rainfall simulator, which consists of pressure-compensating dripper grids above a horizontal mesh that breaks and distributes raindrops, was developed to be applied in wash-off experiments in a large-scale physical model of 36 m2. The mesh typology and size, and its distance to drippers, were established through a calibration where rain uniformity and distributions of raindrop sizes and velocities were compared with local natural rainfall. Finally, the rain properties of the final solution were measured for the three rain intensities that the rainfall simulator is able to generate (30, 50 and 80 mm/h), obtaining almost uniform rainfalls with uniformity coefficients of 81%, 89% and 91%, respectively. This, together with the very suitable raindrop size distribution obtained, and the raindrop velocities of around 87.5% of the terminal velocity for the mean raindrop diameter, makes the proposed solution optimal for wash-off studies, where rain properties are key in the detachment of particles. In addition, the flexibility seen in controlling rain characteristics increases the value of the proposed design in that it is adaptable to a wide range of studies.
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Burt, P. J. A., J. Colvin, and S. M. Smith. "Remote sensing of rainfall by satellite as an aid to Oedaleus senegalensis (Orthoptera: Acrididae) control in the Sahel." Bulletin of Entomological Research 85, no. 4 (December 1995): 455–62. http://dx.doi.org/10.1017/s0007485300032922.
Повний текст джерелаАнотація:
AbstractThe Senegalese grasshopper, Oedaleus senegalensis (Krauss) (Orthoptera: Acrididae), is a major grasshopper pest of subsistence crops in the West African Sahel. In northern Mali, O. senegalensis spends the dry season in the egg stage in the soil and eclosion is triggered by the first rains which usually occur in May and June. Satellite imagery potentially enables rainfall, and hense O. senegalensis eclosion, to be monitored over much wider areas than those possible for ground-based observers. In 1990 and 1991, rain-gauge networks were set up at Mourdiah, northern Mali, and for each storm event, rainfall and Meteosat infra-red data were collected. The coldest convection clouds (< -70°C) produced rain 93.1% (n = 15) of the time, whereas warmer cloud (>- 10°C) produced rain only once (n = 61). The relationship between minimum cloud temperature and log transformed rainfall data was negative and highly significant (P < 0.0005). The maximum rain-gauge separation for reliable point measurements of rainfall was 8 km. Simulated rainfall experiments showed that O. senegalensis eclosion is influenced both by soil type and by the quantity of water added to the soil. A grasshopper survey after the first rain in 1994 showed that 8 mm of rain was sufficient to cause eclosion 9 days later. The implications of these results for improved O. senegalensis control are discussed.
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Xiang, Wen, Guang Fan Li, and Yan Rong Li. "Hainan Tropical Rainforest Landslide Analysis and Prevention Measures." Applied Mechanics and Materials 638-640 (September 2014): 648–51. http://dx.doi.org/10.4028/www.scientific.net/amm.638-640.648.
Повний текст джерелаАнотація:
By Hainan tropical rainforest area geology, physiognomy, the characteristics of climate, tropical rain forest complex typhoon heavy rainfall weather conditions, and the characteristic of the tropical rainforest landslide occurred, researching and analyzing the relationship of among tropical rainforest landslide, tropical rain forest vegetation destruction the relationship ,the heavy rainfall and human engineering activities. Summed up the vegetation destruction, heavy rains and engineering activities of the three factors of coupling is the most important characteristics of tropical rain forests of landslide, and put forward reasonable tropical rainforest landslide protection and management measures.
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Reiser, H., and H. Kutiel. "The rainfall regime and its uncertainty in Valencia and Larnaca." Advances in Geosciences 12 (August 27, 2007): 101–6. http://dx.doi.org/10.5194/adgeo-12-101-2007.
Повний текст джерелаАнотація:
Abstract. The Most Expected Rainfall Regime – MERR in a certain region is composed of various parameters regarding the annual rainfall regime in that region. The present study examines several parameters of the MERR, such as: the rainfall TOTAL, the Date of Accumulated Percentage-DAP, the Rainy Season Length-RSL, the Number of Rain-Spells-NRS, the Rain-Spell Yield-RSY, the ratio between Average and Median rainfall-AMED, the relationship between accumulated precipitation and the number of rain-spells and the Dry-Spell Distribution-DSD. Two stations at the two sides of the Mediterranean basin, Valencia and Larnaca, have been used to illustrate the distribution of the above parameters across the Mediterranean. The main conclusion of the study is that the rainfall regime at Larnaca is less uncertain as compared with the regime in Valencia. This is probably due to the fact that rainfalls are completely absent during the summer in Larnaca, which better suits the definition of a Mediterranean climate than that of Valencia.
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Molina-Sanchis, Isabel, Roberto Lázaro, Eva Arnau-Rosalén, and Adolfo Calvo-Cases. "Rainfall timing and runoff: The influence of the criterion for rain event separation." Journal of Hydrology and Hydromechanics 64, no. 3 (September 1, 2016): 226–36. http://dx.doi.org/10.1515/johh-2016-0024.
Повний текст джерелаАнотація:
Abstract Rain is not uniform in time and space in semiarid areas and its distribution is very important for the runoff process. Hydrological studies usually divide rainfall into events. However, defining rain events is complicated, and rain characteristics vary depending on how the events are delimited. Choosing a minimum inter-event time (MIT) is a commonly used criterion. Our hypothesis is that there will be an optimal MIT that explains the maximum part of the variance of the runoff, with time to runoff used as a surrogate. The objective is to establish a procedure in order to decide upon this optimal MIT. We developed regressions between time to runoff (T0) and three descriptive variables of rain. Our results show that the optimum MIT is 1 hour, which seems to be the minimum period of time required for water in larger macropores to drain and sufficiently modify the effect of antecedent soil moisture on the runoff generation process. Rain events are classified into three significantly different groups: (1) large and intense rains, (2) light rains on wet soil, and (3) light rains on dry soil. Intense rains produce most of the runoff, but there were significant differences between small events in the runoff generated. Of rain events, 63.75% are single-tip events, and many could be dew.
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Bouget, Vincent, Dominique Béréziat, Julien Brajard, Anastase Charantonis, and Arthur Filoche. "Fusion of Rain Radar Images and Wind Forecasts in a Deep Learning Model Applied to Rain Nowcasting." Remote Sensing 13, no. 2 (January 13, 2021): 246. http://dx.doi.org/10.3390/rs13020246.
Повний текст джерелаАнотація:
Short- or mid-term rainfall forecasting is a major task with several environmental applications such as agricultural management or flood risk monitoring. Existing data-driven approaches, especially deep learning models, have shown significant skill at this task, using only rainfall radar images as inputs. In order to determine whether using other meteorological parameters such as wind would improve forecasts, we trained a deep learning model on a fusion of rainfall radar images and wind velocity produced by a weather forecast model. The network was compared to a similar architecture trained only on radar data, to a basic persistence model and to an approach based on optical flow. Our network outperforms by 8% the F1-score calculated for the optical flow on moderate and higher rain events for forecasts at a horizon time of 30 min. Furthermore, it outperforms by 7% the same architecture trained using only rainfall radar images. Merging rain and wind data has also proven to stabilize the training process and enabled significant improvement especially on the difficult-to-predict high precipitation rainfalls.
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Zeng, Yong, Lianmei Yang, Zepeng Tong, Yufei Jiang, Zuyi Zhang, Jinru Zhang, Yushu Zhou, Jiangang Li, Fan Liu, and Jin Liu. "Statistical Characteristics of Raindrop Size Distribution during Rainy Seasons in Northwest China." Advances in Meteorology 2021 (March 6, 2021): 1–12. http://dx.doi.org/10.1155/2021/6667786.
Повний текст джерелаАнотація:
Raindrop size distribution (DSD) is of great significance for understanding the microphysical process of rainfall and the quantitative precipitation estimation (QPE). However, in the past, there was a lack of relevant research on Xinjiang in the arid region of northwest China. In this study, the rainy season data collected by the disdrometer in the Yining area of Xinjiang were used for more than two years, and the characteristics of DSDs for all samples, for two rain types (convective and stratiform), and for six different rain rates were studied. The results showed that nearly 70% of the total samples had a rainfall rate of less than 1 mm·h−1, the convective rain was neither continental nor maritime, and there was a clear boundary between convective rain and stratiform rain in terms of the scattergram of the standardized intercept parameter ( log 10 N w ) versus the mass-weighted average diameter ( D m ). When the raindrop diameter was less than 0.7 mm, DSDs of the two rainfalls basically coincided, while when the raindrop diameter was greater than 0.7 mm, DSDs of convective rainfall were located above the stratiform rain. As the rainfall rate increased, D m increased, while log 10 N w first increased and then decreased. In addition, we deduced the Z − R (radar reflectivity-rain rate) relationship and μ − Λ relationship (shape parameter-slope parameter of the gamma DSDs) suitable for the Yining area. These conclusions are conducive to strengthening the understanding of rainfall microphysical processes in arid regions and improving the ability of QPE in arid regions.
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Islam, Md Nazrul, Someshwar Das, and Hiroshi Uyeda. "Calibration of TRMM Derived Rainfall Over Nepal During 1998-2007." Open Atmospheric Science Journal 4, no. 1 (January 19, 2010): 12–23. http://dx.doi.org/10.2174/1874282301004010012.
Повний текст джерелаАнотація:
In this study rainfall is calculated from Tropical Rainfall Measuring Mission (TRMM) Version 6 (V6) 3B42 datasets and calibrated with reference to the observed daily rainfall by rain-gauge collected at 15 locations over Nepal during 1998-2007. In monthly, seasonal and annual scales TRMM estimated rainfalls follow the similar distribution of historical patterns obtained from the rain-gauge data. Rainfall is large in the Southern parts of the country, especially in the Central Nepal. Day-to-day rainfall comparison shows that TRMM derived trend is very similar to the observed data but TRMM usually underestimates rainfall on many days with some exceptions of overestimation on some days. The correlation coefficient of rainfalls between TRMM and rain-gauge data is obtained about 0.71. TRMM can measure about 65.39% of surface rainfall in Nepal. After using calibration factors obtained through regression expression the TRMM estimated rainfall over Nepal becomes about 99.91% of observed data. TRMM detection of rainy days is poor over Nepal; it can approximately detect, under-detect and over-detect by 19%, 72% and 9% of stations respectively. False alarm rate, probability of detection, threat score and skill score are calculated as 0.30, 0.68, 0.53 and 0.55 respectively. Finally, TRMM data can be utilized in measuring mountainous rainfall over Nepal but exact amount of rainfall has to be calculated with the help of adjustment factors obtained through calibration procedure. This preliminary work is the preparation of utilization of Global Precipitation Measurement (GPM) data to be commencing in 2013.
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Yu, Zifeng, Yuqing Wang, Haiming Xu, Noel Davidson, Yandie Chen, Yimin Chen, and Hui Yu. "On the Relationship between Intensity and Rainfall Distribution in Tropical Cyclones Making Landfall over China." Journal of Applied Meteorology and Climatology 56, no. 10 (October 2017): 2883–901. http://dx.doi.org/10.1175/jamc-d-16-0334.1.
Повний текст джерелаАнотація:
AbstractTRMM satellite 3B42 rainfall estimates for 133 landfalling tropical cyclones (TCs) over China during 2001–15 are used to examine the relationship between TC intensity and rainfall distribution. The rain rate of each TC is decomposed into axisymmetric and asymmetric components. The results reveal that, on average, axisymmetric rainfall is closely related to TC intensity. Stronger TCs have higher averaged peak axisymmetric rain rates, more averaged total rain, larger averaged rain areas, higher averaged rain rates, higher averaged amplitudes of the axisymmetric rainfall, and lower amplitudes of wavenumbers 1–4 relative to the total rainfall. Among different TC intensity change categories, rapidly decaying TCs show the most rapid decrease in both the total rainfall and the axisymmetric rainfall relative to the total rain. However, the maximum total rain, maximum rain area, and maximum rain rate are not absolutely dependent on TC intensity, suggesting that stronger TCs do not have systematically higher maximum rain rates than weaker storms. Results also show that the translational speed of TCs has little effect on the asymmetric rainfall distribution in landfalling TCs. The maximum rainfall of both the weaker and stronger TCs is generally located downshear to downshear left. However, when environmental vertical wind shear (VWS) is less than 5 m s−1, the asymmetric rainfall maxima are more frequently located upshear and onshore, suggesting that in weak VWS environments the coastline could have a significant effect on the rainfall asymmetry in landfalling TCs.
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Zhou, Y. P., W. K. Tao, A. Y. Hou, W. S. Olson, C. L. Shie, K. M. Lau, M. D. Chou, X. Lin, and M. Grecu. "Use of High-Resolution Satellite Observations to Evaluate Cloud and Precipitation Statistics from Cloud-Resolving Model Simulations. Part I: South China Sea Monsoon Experiment." Journal of the Atmospheric Sciences 64, no. 12 (December 1, 2007): 4309–29. http://dx.doi.org/10.1175/2007jas2281.1.
Повний текст джерелаАнотація:
Abstract Cloud and precipitation simulated using the three-dimensional (3D) Goddard Cumulus Ensemble (GCE) model are compared to Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Precipitation Radar (PR) rainfall measurements and Clouds and the Earth’s Radiant Energy System (CERES) single scanner footprint (SSF) radiation and cloud retrievals. Both the model simulation and retrieved parameters are based upon observations made during the South China Sea Monsoon Experiment (SCSMEX) field campaign. The model-simulated cloud and rain systems are evaluated by systematically examining important parameters such as the surface rain rate, convective/stratiform percentage, rain profiles, cloud properties, and precipitation efficiency. It is demonstrated that the GCE model is capable of simulating major convective system development and reproduces the total surface rainfall amount as compared to rainfall estimated from the SCSMEX sounding network. The model yields a slightly higher total convective rain/stratiform rain ratio than the TMI and PR observations. The GCE rainfall spectrum exhibits a greater contribution from heavy rains than those estimated from PR or TMI observations. In addition, the GCE simulation produces much greater amounts of snow and graupel than the TRMM retrievals. The model’s precipitation efficiency of convective rain is close to the observations, but the precipitation efficiency of stratiform rain is much lower than the observations because of large amounts of slowly falling simulated snow and graupel. Compared to observations, the GCE produces more compact areas of intense convection and less anvil cloud, which are consistent with a smaller total cloud fraction and larger domain-averaged outgoing longwave radiation.
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Khansa, Pavita, Evi Siti Sofiyah, and I. Wayan Koko Suryawan. "Determination of Rain Intensity Based on Rain Characteristics Observed from Rain Observation Stations Around South Jakarta." Journal of Advanced Civil and Environmental Engineering 3, no. 2 (October 15, 2020): 94. http://dx.doi.org/10.30659/jacee.3.2.106-115.
Повний текст джерелаАнотація:
South Jakarta has the highest rainfall concentration and the most flood location in Jakarta. Therefore, an urban drainage system is needed to control surface water so flood can be prevented. This research aims to support the urban drainage system planning by determining rainfall intensity based on three methods, those are Van Breen, Bell Tanimoto, and Hasper der Weduwen. The most suitable method will be selected by comparing the value of rainfall intensity with Talbot, Sherman, and Ishiguro approach. This research reveals that the most suitable method is the Van Breen Method with the Talbot equation. The result of the calculation is rainfall intensity for 2, 5, 10, 25, 50, and 100 years rain return period, with each range 27.2 – 182.8 mm/hour, 36.8-197.6 mm/hour, 43.1-206.3 mm/hour, 51.1-216.6 mm/hour, 57-223.9 mm/hour, and 63-230,8 mm/hour.
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Jiang, Haiyan, Jeffrey B. Halverson, Joanne Simpson, and Edward J. Zipser. "Hurricane “Rainfall Potential” Derived from Satellite Observations Aids Overland Rainfall Prediction." Journal of Applied Meteorology and Climatology 47, no. 4 (April 1, 2008): 944–59. http://dx.doi.org/10.1175/2007jamc1619.1.
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Abstract The Tropical Rainfall Measuring Mission–based National Aeronautics and Space Administration Goddard Multisatellite Precipitation Analysis (MPA) product is used to quantify the rainfall distribution in tropical cyclones that made landfall in the United States during 1998–2004. A total of 37 tropical cyclones (TC) are examined, including 2680 three-hourly MPA precipitation observations. Rainfall distributions for overland and overocean observations are compared. It is found that the TC rainfall over ocean bears a strong relationship with the TC maximum wind, whereas the relationship for overland conditions is much weaker. The rainfall potential is defined by using the satellite-derived rain rate, the satellite-derived storm size, and the storm translation speed. This study examines the capability of the overocean rainfall potential to predict a storm’s likelihood of producing heavy rain over land. High correlations between rain potentials before landfall and the maximum storm total rain over land are found using the dataset of the 37 landfalling TCs. Correlations are higher with the average rain potential on the day prior to landfall than with averages over any other time period. A TC overland rainfall index is introduced based on the rainfall potential study. This index can be used to predict the storm peak rainfall accumulation over land. Six landfalling storms during the 2005 Atlantic Ocean hurricane season are examined to verify the capability of using this index to forecast the maximum storm total rain over land in the United States. The range of the maximum storm overland rain forecast error for these six storms is between 2.5% and 24.8%.
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Sudirman, Ilham, and Alamsyah. "Land Gradation Effect Analysis on Permeability and Ponding Time on Repeat Rain Frequency: Laboratory Study with Rainfall Simulator." Journal La Multiapp 1, no. 1 (January 30, 2020): 10–17. http://dx.doi.org/10.37899/journallamultiapp.v1i1.35.
Повний текст джерелаАнотація:
Analysis of Effect of Land Gradation on Permeability and Ponding Time in Frequency of Repeated Rain (Laboratory Studies with Rainfall Simulator) guided by Darwis Panguriseng and Mahmuddin. That soil permeability is the ability of soil to pass water or air. Soil permeability is usually measured in terms of the speed of water flowing in a certain time specified in units of cm/hour. Ponding time (tp) is the time difference between when it rains and the time when water begins to pool above ground level. The purpose of this study was to determine the effect of soil grading on permeability and inundation time with repeated frequency of rainfall with the same intensity on mixed soil types. This research method is a type of laboratory experimental research, using a rainfall simulator. The soil used in this study is mixed soil types. Furthermore, artificial rain is given with an intensity of I15, each intensity is used five times the frequency of rain and the inundation time readings and inundation height are carried out in the Rainfall Simulator experiment tank and for the permeability test, observation is done with the constant head test. The results showed the value of the permeability coefficient is inversely proportional to the increase in rainfall intensity and frequency of rain. Inundation height and final inundation time are directly proportional to increasing rainfall intensity and rainfall frequency.
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Chen, Guixing, Ruoyu Lan, Wenxin Zeng, He Pan, and Weibiao Li. "Diurnal Variations of Rainfall in Surface and Satellite Observations at the Monsoon Coast (South China)." Journal of Climate 31, no. 5 (March 2018): 1703–24. http://dx.doi.org/10.1175/jcli-d-17-0373.1.
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The complex features of rainfall diurnal cycles at the south China coast are examined using hourly rain gauge data and satellite products (CMORPH and TRMM 3B42) during 1998–2014. It is shown that morning rainfall is pronounced near the coasts and windward mountains, with high rainfall in the summer monsoon season, while afternoon rainfall is dominant on land, and nocturnal rainfall occurs at northern inland sites. Both satellite products report less morning rainfall and more afternoon rainfall than the rain gauge data, and they also miss the midnight rainfall minimum. These errors are mainly attributable to an underestimation of morning moderate and intense rains at coasts and an overestimation of afternoon–evening light rains on land. With a correction of the systematic bias, satellite products faithfully resolve the spatial patterns of normalized rainfall diurnal cycles related to land–sea contrast and terrains, suggesting an improved data application for regional climate studies. In particular, they are comparable to the rain gauge data in showing the linear reduction of morning rainfall from coasts to inland regions. TRMM is marginally better than CMORPH in revealing the overall features of diurnal cycles, while higher-resolution CMORPH captures more local details. All three datasets also present that morning rainfall decreases from May–June to July–August, especially on land; it exhibits pronounced interannual variations and a decadal increase in 1998–2008 at coasts. Such long-term variations of morning rainfall are induced by the coastal convergence and mountain liftings of monsoon shear flow interacting with land breeze, which is mainly regulated by monsoon southwesterly winds in the northern part of the South China Sea.
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Setyowati, Dewi Liesnoor. "Hubungan Hujan dan Limpasan Pada Sub DAS Kecil Penggunaan Lahan Hutan, Sawah, Kebun Campuran di DAS Kreo." Forum Geografi 24, no. 1 (July 20, 2010): 39. http://dx.doi.org/10.23917/forgeo.v24i1.5014.
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Tendency of land use conversion is followed by maximum discharge of Kreo River, but unknown land use type what which can race improvement of runoff. Purpose of the research is study the relation of rainfall runoff at forest, rice field, and mixed garden. Research about rainfall runoff study is including research type of experiment for purpose of descriptive, through observation of rain data and water level at small watershed with one land use types that is forest, rice field, and mixed garden. Instrument of rain and water level attached at small watershed during the rains 2007.Data analysis comprises analysis of stream hydrograph, rain analysis, stream coefficient, and statistic analysis as well. Big the so small runoff value is more determined by rainfall amounts happened non land use type. Number of big rains at one land use will yield big runoff also, while the same rainfall amounts at some land use types will yield varying runoff follows land use type and condition of soil At small watershed (less than 200 ha), the relation of rainfall (P) with direct runoff (DRO) has very strong correlation (R2 bigger than 0.7). Relation between rain intensity (I) with DRO; I with peak discharge (Qp); duration of rain (DR) with DRO; DR with Qp indicated weak reaction (R2 less than 0.3). It indicated there were many factors (more than 70%) which influenced the above mentioned relations. Runoff coefficient value at forest was 0,3566, mix forest was 0,4227, rice field was 0,6661, and mixed garden was 0,4227. Land ability to permeate in the forest (65%) is bigger than mixed garden (57%) and rice field (33%).
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Sinatra, T., A. Awaludin, F. Nauval, and C. Purnomo. "Calibration of Spatial Rain Scanner using Rainfall Depth of Rain Gauges." IOP Conference Series: Earth and Environmental Science 893, no. 1 (November 1, 2021): 012064. http://dx.doi.org/10.1088/1755-1315/893/1/012064.
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Abstract A spatial rain scanner has been developed based on a marine radar to satisfy the demand for spatial rain information for hydrological applications. Since the coverage of the rain scanner is 44 km in radius, it is necessary to expand the coverage by installing it in two sites that intersect each other performing a radar network. For this purpose, the first rain scanner has been installed at the Center for Atmospheric Science and Technology (PSTA) in Bandung and the second one at the Space and Atmospheric Observation Center (BPAA) Tanjungsari in Sumedang. This paper focuses on the calibration of radar observations with rainfall data from 7 rain gauges installed in Bandung area and its surroundings. The calibration method calculates rainfall depth (three parameters) instead of only the intensity of rainfall. The data period used for this research is from March to November 2020. The rain scanners have better rainfall events detection over basin area, such as Dayeuh Kolot and Cidurian, than over highland area, such as Lembang. Two calibration methods are used, and the results show that the calibration by calculating three parameters (accumulated reflectivity, duration, and intensity) in the linear model is able to measure rainfall estimation better than using a linear model with one parameter (accumulated reflectivity) for rainfall depth more than 10 mm. Rainfall estimation calculation using scheme 1 tends to underestimate while scheme 2 tends to overestimate.
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Mapiam, Punpim Puttaraksa, Monton Methaprayun, Thom Bogaard, Gerrit Schoups, and Marie-Claire Ten Veldhuis. "Citizen rain gauges improve hourly radar rainfall bias correction using a two-step Kalman filter." Hydrology and Earth System Sciences 26, no. 3 (February 11, 2022): 775–94. http://dx.doi.org/10.5194/hess-26-775-2022.
Повний текст джерелаАнотація:
Abstract. The low density of conventional rain gauge networks is often a limiting factor for radar rainfall bias correction. Citizen rain gauges offer a promising opportunity to collect rainfall data at a higher spatial density. In this paper, hourly radar rainfall bias adjustment was applied using two different rain gauge networks: tipping buckets, measured by Thai Meteorological Department (TMD), and daily citizen rain gauges. The radar rainfall bias correction factor was sequentially updated based on TMD and citizen rain gauge data using a two-step Kalman filter to incorporate the two gauge datasets of contrasting quality. Radar reflectivity data from the Sattahip radar station, gauge rainfall data from the TMD, and data from citizen rain gauges located in the Tubma Basin, Thailand, were used in the analysis. Daily data from the citizen rain gauge network were downscaled to an hourly resolution based on temporal distribution patterns obtained from radar rainfall time series and the TMD gauge network. Results show that an improvement in radar rainfall estimates was achieved by including the downscaled citizen observations compared with bias correction based on the conventional rain gauge network alone. These outcomes emphasize the value of citizen rainfall observations for radar bias correction, in particular in regions where conventional rain gauge networks are sparse.
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Thomaz, Edivaldo Lopes, and Valdemir Antoneli. "RAIN INTERCEPTION IN A SECONDARY FRAGMENT OF ARAUCARIA FOREST WITH FAXINAL, GUARAPUAVA-PR." CERNE 21, no. 3 (September 2015): 363–69. http://dx.doi.org/10.1590/01047760201521031736.
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ABSTRACT Forest management can alter the structure of vegetation (layer), particularly in areas used for pasture, such as the Faxinal areas in the south central region of Paraná, Brazil. Therefore, the aims of the present study were as follows: a) to assess rain interception in secondary forests; b) to estimate the maximum precipitation intercepted by the forest; and c) to discuss the possible implications of throughfall for the hydrologic processes of the secondary forest (Faxinal). Nine 20-cm-diameter rain gauges (314 cm2) were used. Rain gauges were distributed randomly throughout the forest and were successively rotated after a specific number of rainfalls. A total of 66 rainfall events of different volumes were recorded. We observed that an increase in rain volume tended to homogenize the rainfall interception rate in the forest. Consecutive rainfalls did not significantly influence the interception rate in the secondary forest. However, the interception in the secondary forest (10.5%) was lower than the mean interception rate recorded in other Brazilian forests.
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Peleg, N., M. Ben-Asher, and E. Morin. "Radar subpixel-scale rainfall variability and uncertainty: lessons learned from observations of a dense rain-gauge network." Hydrology and Earth System Sciences 17, no. 6 (June 14, 2013): 2195–208. http://dx.doi.org/10.5194/hess-17-2195-2013.
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Abstract. Runoff and flash flood generation are very sensitive to rainfall's spatial and temporal variability. The increasing use of radar and satellite data in hydrological applications, due to the sparse distribution of rain gauges over most catchments worldwide, requires furthering our knowledge of the uncertainties of these data. In 2011, a new super-dense network of rain gauges containing 14 stations, each with two side-by-side gauges, was installed within a 4 km2 study area near Kibbutz Galed in northern Israel. This network was established for a detailed exploration of the uncertainties and errors regarding rainfall variability within a common pixel size of data obtained from remote sensing systems for timescales of 1 min to daily. In this paper, we present the analysis of the first year's record collected from this network and from the Shacham weather radar, located 63 km from the study area. The gauge–rainfall spatial correlation and uncertainty were examined along with the estimated radar error. The nugget parameter of the inter-gauge rainfall correlations was high (0.92 on the 1 min scale) and increased as the timescale increased. The variance reduction factor (VRF), representing the uncertainty from averaging a number of rain stations per pixel, ranged from 1.6% for the 1 min timescale to 0.07% for the daily scale. It was also found that at least three rain stations are needed to adequately represent the rainfall (VRF < 5%) on a typical radar pixel scale. The difference between radar and rain gauge rainfall was mainly attributed to radar estimation errors, while the gauge sampling error contributed up to 20% to the total difference. The ratio of radar rainfall to gauge-areal-averaged rainfall, expressed by the error distribution scatter parameter, decreased from 5.27 dB for 3 min timescale to 3.21 dB for the daily scale. The analysis of the radar errors and uncertainties suggest that a temporal scale of at least 10 min should be used for hydrological applications of the radar data. Rainfall measurements collected with this dense rain gauge network will be used for further examination of small-scale rainfall's spatial and temporal variability in the coming years.
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ADIKANT PRADHAN, T. CHANDRAKAR, S.K. NAG, A. DIXIT, and S.C. MUKHERJEE. "Crop planning based on rainfall variability for Bastar region of Chhattisgarh, India." Journal of Agrometeorology 22, no. 4 (December 1, 2021): 509–17. http://dx.doi.org/10.54386/jam.v22i4.477.
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 Analysis of long-term rainfall data (1986-2018) of Bastar region revealed decreasing trend in total quantum of annual rainfall with varying frequency and distribution. The quantity of winter and summer rains decreased drastically during 2008-18 as compared to earlier two decades (1986-96 and 1997-2007). SW monsoon rain of 2008-18 was more than past two decades, whereas NE monsoon rain changed much in quantity except during 1997-2007. During 1986-96, the pre-monsoon shower was received in April, but later two decades the shower was received in May, which supports for summer ploughing and dry aerobic seeding. The cropping period almost synchronized between 22-43 standard meteorological week (SMW) reaching 93.11 mm per week as maximum rainfall. As the probability of 20 mm rainfall decreased from 75 to 50%, the crop yield got reduced by 30%. The mid-land rice with a probability of 13.47 to 16.07 mm rain per week supported growth phase during 17-21SMW. Whereas, upland rice maturing in 90-100 days could avoid dry spells, if the rice is managed by conservation furrows at the time of sowing. The summer ploughing is preferred with more than 40 mm rain in single day during March to April for mitigating dry spells. On the other hand, preparatory tillage and sowing were performed together in support of ripening niger and horsegram under probability of 75, 50 and 25% rain through crop planning. Maize and small millets reduced yield significantly when rainfall reached 75% deficit, whereas 25% deficit rain did not affect the yields.
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Westcott, Nancy E., Steven E. Hollinger, and Kenneth E. Kunkel. "Use of Real-Time Multisensor Data to Assess the Relationship of Normalized Corn Yield with Monthly Rainfall and Heat Stress across the Central United States." Journal of Applied Meteorology 44, no. 11 (November 1, 2005): 1667–76. http://dx.doi.org/10.1175/jam2303.1.
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Abstract This study evaluated the suitability of rain estimates based on the National Weather Service (NWS) Weather Surveillance Radar-1988 Doppler (WSR-88D) network to estimate yield response to rainfall on a county scale and to provide real-time information related to crop stress resulting from deficient or excessive precipitation throughout the summer. The relationship between normalized corn yield and rainfall was examined for nine states in the central United States for 1997–99 and 2001–02. Monthly rainfall estimates were computed employing multisensor precipitation estimate (MPE) data from the National Centers for Environmental Prediction and quality-controlled (QC_Coop) and real-time (RT_Coop) NWS cooperative gauge data. In-season MPE rain estimates were found to be of comparable quality to the postseason QC_Coop estimates for predicting county corn yields. Both MPE and QC_Coop estimates were better related to corn yield than were RT_Coop estimates, presumably because of the lower density of RT_Coop gauges. Large corn yields typically resulted when May rain was less than 125 mm and July rain was greater than 50 mm. Low yields often occurred when July rainfall was less than 100 mm. For moderate July rains (50–100 mm), positive and negative normalized yields resulted. Parameterization of heat stress (number of July days &gt; 32.2°C) improved the correlation between rainfall and normalized corn yield, particularly for years with the poorest yield-vs-rain relationship (1998 and 1999). For the combined analysis years, the multiple regression correlation coefficient was 0.56, incorporating May and July rainfall and July heat stress and explaining 31% of the variance of normalized corn yield. Results show that MPE rainfall estimates provide timely yield projections within the growing season.
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Minda, Haruya, and Kenji Nakamura. "High Temporal Resolution Path-Average Rain Gauge with 50-GHz Band Microwave." Journal of Atmospheric and Oceanic Technology 22, no. 2 (February 1, 2005): 165–79. http://dx.doi.org/10.1175/jtech-1683.1.
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Abstract Rain radar measures instantaneous spatial-average rainfall, while conventional rain gauges directly measure point rainfall with low temporal resolution. Thus differences in the resolution of the sensors create difficulties for rain radar validation, especially for spaceborne rain radar. Accordingly, rainfall measurement by microwave link has been proposed for several decades, as it estimates instantaneous path-average rainfall. Thus it is expected that the microwave link rain gauge will overcome, at least partly, the problems in the rain radar validation, toward which a 50-GHz band microwave link [the path-averaged rain gauge (PRG)] was developed that has been in operation since September 2000. In this paper, the authors show the potential of the PRG system by a simple model and rainfall comparison with a disdrometer and a tipping-bucket rain gauge. Differences observed by the instruments were within 15% (within 10% in half of the cases) during actual rain events in 2003. This confirmed that the PRG system displayed good performance as a rain gauge. Finally, the possibility of the PRG system being applied for spaceborne rain radar validation is considered.
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Song, Hwan-Jin, Byunghwan Lim, and Sangwon Joo. "Evaluation of Rainfall Forecasts with Heavy Rain Types in the High-Resolution Unified Model over South Korea." Weather and Forecasting 34, no. 5 (September 9, 2019): 1277–93. http://dx.doi.org/10.1175/waf-d-18-0140.1.
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Abstract Heavy rainfall events account for most socioeconomic damages caused by natural disasters in South Korea. However, the microphysical understanding of heavy rain is still lacking, leading to uncertainties in quantitative rainfall prediction. This study is aimed at evaluating rainfall forecasts in the Local Data Assimilation and Prediction System (LDAPS), a high-resolution configuration of the Unified Model over the Korean Peninsula. The rainfall of LDAPS forecasts was evaluated with observations based on two types of heavy rain events classified from K-means clustering for the relationship between surface rainfall intensity and cloud-top height. LDAPS forecasts were characterized by more heavy rain cases with high cloud-top heights (cold-type heavy rain) in contrast to observations showing frequent moderate-intensity rain systems with relatively lower cloud-top heights (warm-type heavy rain) over South Korea. The observed cold-type and warm-type events accounted for 32.7% and 67.3% of total rainfall, whereas LDAPS forecasts accounted for 65.3% and 34.7%, respectively. This indicates severe overestimation and underestimation of total rainfall for the cold-type and warm-type forecast events, respectively. The overestimation of cold-type heavy rainfall was mainly due to its frequent occurrence, whereas the underestimation of warm-type heavy rainfall was affected by both its low occurrence and weak intensity. The rainfall forecast skill for the warm-type events was much lower than for the cold-type events, due to the lower rainfall intensity and smaller rain area of the warm-type. Therefore, cloud parameterizations for warm-type heavy rain should be improved to enhance rainfall forecasts over the Korean Peninsula.
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Wang, Yingjue, Jiafeng Zheng, Zhigang Cheng, and Bingyun Wang. "Characteristics of Raindrop Size Distribution on the Eastern Slope of the Tibetan Plateau in Summer." Atmosphere 11, no. 6 (May 28, 2020): 562. http://dx.doi.org/10.3390/atmos11060562.
Повний текст джерелаАнотація:
Precipitation microphysics over the Tibetan Plateau (TP) remain insufficiently understood, due to the lack of observations and studies. This paper presents a comprehensive investigation of the raindrop size distribution (DSD) for rainfall that happened on the eastern slope of TP in summer. DSD differences between different rain types and under different rain rates are investigated. Confidential empirical relationships between the gamma shape and slope parameters, and between reflectivity and rain rate are proposed. DSD properties in this area are also compared with those in other areas. The results indicate that the stratiform and convective rains contribute to different rain duration and amount, with diverse rainfall macro- and microphysical properties. The rain spectra of two rain types can become broader with higher concentrations as the rain rate increases. DSDs in this area are different to those in other areas. The stratiform DSD is narrower than that in the non-plateau area. The two rain types of this area both have higher number concentrations for 0.437–1.625 mm raindrops than those of the mid-TP. The relationships of shape–slope parameters and reflectivity–rain rate in this area are also different from those in other areas. The rain spectra in this area can produce a larger slope parameter under the same shape parameter than in the mid-TP. The convective rain can produce a smaller rain rate under the same reflectivity. The accuracy proposed reflectivity–rain rate relationship in application to quantitative rainfall estimation is also discussed. The results show that the relationship has an excellent performance when the rain rate exceeds 1 mm h−1.
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Hwang, Seokhwan, Narae Kang, and Jung Soo Yoon. "Error Generation Characteristics of the Areal Rainfall Estimation Interpolation Method Using Rainfall Radar Data." Journal of the Korean Society of Hazard Mitigation 22, no. 6 (December 31, 2022): 273–83. http://dx.doi.org/10.9798/kosham.2022.22.6.273.
Повний текст джерелаАнотація:
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.
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Hu, Caihong, Chengshuai Liu, Yichen Yao, Qiang Wu, Bingyan Ma, and Shengqi Jian. "Evaluation of the Impact of Rainfall Inputs on Urban Rainfall Models: A Systematic Review." Water 12, no. 9 (September 5, 2020): 2484. http://dx.doi.org/10.3390/w12092484.
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Over the past several decades, urban flooding and other water-related disasters have become increasingly prominent and serious. Although the urban rain flood model’s benefits for urban flood simulation have been extensively documented, the impact of rainfall input to model simulation accuracy remains unclear. This systematic review aims to provide structured research on how rain inputs impact urban rain flood model’s simulation accuracy. The selected 48 peer-reviewed journal articles published between 2015 and 2019 on the Web of Science™ database were analyzed by key factors, including rainfall input type, calibration times and verification times. The results from meta-analysis reveal that when a traditional rain measurement was used as the rainfall input, model simulation accuracy was higher, i.e., the Nash–Sutcliffe efficiency coefficient (NSE) of traditional technology for rain measurement was higher than the 0.18 for the new technology rain measurement with respect to flow simulation. In addition, the single-field sub-flood calibration model was better than the multi-field sub-flood calibration model. NSE was higher than 0.14. The precision was better for the verification period; NSE of the calibration value showed a 0.07 higher verification value on average in flow simulation. These findings have certain significance for the development of future urban rain flood models and propose the development direction of the future urban rain flood model. Finally, in view of the rainfall input problem of the urban storm flood model, we propose the future development direction of the urban storm flood model.
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Song, Kun, Xichuan Liu, and Taichang Gao. "Real-Time Rainfall Estimation Using Microwave Links: A Case Study in East China during the Plum Rain Season in 2020." Sensors 21, no. 3 (January 28, 2021): 858. http://dx.doi.org/10.3390/s21030858.
Повний текст джерелаАнотація:
Accurate and real-time rainfall estimation is a pressing need for forecasting the flood disaster and reducing the loss. In this study, we exploit the potential of estimating the rainfall by microwave links in East China. Eight microwave links at 15 GHz and 23 GHz, operated by China Mobile, are used for estimating the rain rate in real-time in Jiangyin, China from June to July 2020. First, we analyze the correlation between the rain-induced attenuation of microwave links and the rain rate measured by rain gauges. The correlation coefficient values are higher than 0.77 with the highest one over 0.9, showing a strong positive correlation. The real-time results indicate that microwave links estimate the rainfall with a higher temporal resolution than the rain gauges. Meanwhile, the rain rate that was estimated by microwave links also correlates well with the actual rain rate, and most of the values of the mean absolute error are less than 1.50 mm/h. Besides, the total rainfall’s relative deviation values are less than 5% with the smallest one reaching 1%. The quantitative results also indicate that microwave links could lead to better forecasting of water levels and, hence, better warnings for flood disasters.
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Lestari, Sopia, Alain Protat, Valentin Louf, Andrew King, Claire Vincent, and Shuichi Mori. "Subdaily Rain-Rate Properties in Western Java Analyzed Using C-Band Doppler Radar." Journal of Applied Meteorology and Climatology 61, no. 9 (September 2022): 1179–99. http://dx.doi.org/10.1175/jamc-d-21-0041.1.
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Abstract Jakarta, a megacity in Indonesia, experiences recurrent floods associated with heavy rainfall. Characteristics of subdaily rainfall and the local factors influencing rainfall around Jakarta have not been thoroughly investigated, primarily because of data limitations. In this study, we examine the frequency and intensity of hourly and daily rain rate, including spatial characteristics and variations across time scales. We use 6-min C-band Doppler radar and 1-min in situ data during 2009–12 to resolve spatial rain-rate characteristics at higher resolution than previous studies. A reflectivity–rain rate (Z–R) relationship is derived (Z = 102.7R1.75) and applied to estimate hourly rain rate. Our results show that rain rate around Jakarta is spatially inhomogeneous. In the rainy season [December–February (DJF)], rain rate exhibits statistical properties markedly different from other seasons, with much higher frequency of rain, but, on average, less intense rain rate. In all seasons, there is a persistent higher hourly and daily mean rain rate found over mountainous areas, indicating the importance of local orographic effects. In contrast, for hourly rain-rate extremes, peaks are observed mostly over the coastal land and lowland areas. For the diurnal cycle of mean rain rate, a distinct afternoon peak is found developing earlier in DJF and later in the dry season. This study has implications for other analyses of mesoscale rain-rate extremes in areas of complex topography and suggests that coarse-grain products may miss major features of the rain-rate variability identified in our study. Significance Statement For many years, Jakarta and its surrounding regions have been repeatedly inundated by flooding triggered by short-duration heavy rainfall or rainfall accumulated over multiple days. Little is known about the distribution of local rainfall and how it differs between seasons. In this study, we used high-resolution C-band Doppler radar during 2009–12 to understand the characteristics of rainfall over this complex topography. The results demonstrate that the rainfall features vary spatially and seasonally. In the wet season, rainfall is more frequent but, on average, lighter relative to other seasons. In all seasons, the highest hourly and daily mean rain rate persistently occurs over the mountains, indicating the vital role of topography in generating rainfall in the region.
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Oyaro, J., and J. Ben-Edigbe. "The Extent of Capacity Loss Caused by Rainfall at Signalised Intersections." Open Transportation Journal 14, no. 1 (December 21, 2020): 214–21. http://dx.doi.org/10.2174/1874447802014010214.
Повний текст джерелаАнотація:
Background: Even though their physical characteristics exert a constant influence on capacity and saturation flows, signalized intersections are fixed facilities not affected by rainfall. Whilst traffic conditions with varying effects can be regulated, rainfall conditions cannot be regulated but compensated for by warning drivers to reduce speed. Speed reduction has an impact on signalised intersection capacity, whilst signalised intersection capacity is a function of saturation flow, effective green, and cycle time. In this paper, a capacity loss is the differential percentage between ‘with and without’ rainfall scenario. Aim: The paper investigated the extent of capacity loss caused by rainfall at signalised intersections. Methods: In Durban, South Africa, rainfall data were collected, collated, and correlated with traffic data in a 'with and without' rainfall intensity study. Rainfall intensity was classified according to the rate of precipitation as follows; rainfall intensity(i): light rain (i <2.5mm/h); Moderate rain (2.5mm/h ≤ i < 10mm/h), and heavy rain (10 ≤ i ≤ 50mm/h) as prescribed by the World Meteorological Society. Results: Empirical results show that rainfall intensity has an effect on road capacity at a signalised intersection. Generally, for the vehicles going straight, light rain caused a 4.25% capacity loss; moderate rain 9.18% while heavy rain caused an 11.53% capacity reduction. With right-turning vehicles, light rain caused 7.38% capacity loss; moderate rain caused 14.3%, while heavy rain accounted for 19.15% capacity reduction. Conclusion: The paper concluded that rainfall at signalised intersections would cause an anomalous capacity reduction. Since the database for the study is small, the paper advocates for further studies based on a broader database to include yellow interval time.
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Chakraborty, Arindam, and T. N. Krishnamurti. "Improving Global Model Precipitation Forecasts over India Using Downscaling and the FSU Superensemble. Part II: Seasonal Climate." Monthly Weather Review 137, no. 9 (September 1, 2009): 2736–57. http://dx.doi.org/10.1175/2009mwr2736.1.
Повний текст джерелаАнотація:
Abstract This study addresses seasonal forecasts of rains over India using the following components: high-resolution rain gauge–based rainfall data covering the years 1987–2001, rain-rate initialization, four global atmosphere–ocean coupled models, a regional downscaling of the multimodel forecasts, and a multimodel superensemble that includes a training and a forecast phase at the high resolution over the internal India domain. The results of monthly and seasonal forecasts of rains for the member models and for the superensemble are presented here. The main findings, assessed via the use of RMS error, anomaly correlation, equitable threat score, and ranked probability skill score, are (i) high forecast skills for the downscaled superensemble-based seasonal forecasts compared to the forecasts from the direct use of large-scale model forecasts were possible; (ii) very high scores for rainfall forecasts have been noted separately for dry and wet years, for different regions over India and especially for heavier rains in excess of 15 mm day−1; and (iii) the superensemble forecast skills exceed that of the benchmark observed climatology. The availability of reliable measures of high-resolution rain gauge–based rainfall was central for this study. Overall, the proposed algorithms, added together, show very promising results for the prediction of monsoon rains on the seasonal time scale.
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Azwar, Azwar, Ella Meilianda, and Masimin Masimin. "KAJIAN POLA CURAH HUJAN DURASI PANJANG TERKAIT DENGAN WAKTU KEJADIAN BANJIR DI KABUPATEN ACEH UTARA." Jurnal Arsip Rekayasa Sipil dan Perencanaan 4, no. 1 (January 25, 2022): 39–48. http://dx.doi.org/10.24815/jarsp.v4i1.16723.
Повний текст джерелаАнотація:
North Aceh Regency almost every year experiences flooding due to heavy rains, both due to rain in the area and flooding of shipments due to heavy rains in neighboring districts namely Bener Meriah. Judging from the time of the incident, heavy rains always occur in the final months of each year. The duration of rainfall is two, namely: (a) short duration and (b) long duration. The second limit is the duration of rain 24 hours (1 day), so that the duration of rainfall is long if the time of occurrence is longer than 24 hours. For tropical climates such as the Aceh region known to experience two seasons, namely: a) the rainy season and b) the dry season in terms of climatology, the rainy season is identical to the occurrence of flooding. The dry season or rainy season are related to the time of year, for example the flood season occurs in the final months of each year, the dry season occurs in the middle of the year, especially for the North Aceh region. The objectives of this study are (a) to obtain information on the relatively heavy rainfall distribution pattern for long duration rainfall events, namely 1-day, 3-day, 5-day and 7-daily. (b) Knowing the timing of flood events is calculated based on the movement of the sun. The data used is daily rainfall data obtained from the Lhokseumawe Meteorological Station from 1986 to 2016. The results of the analysis are to find out the maximum rainfall for 1-day, 3-day, 5-day, and 7 daily. Because what was investigated was the pattern of rain, the partial series method was used, namely the possibility of some data being taken in one year. The results of processing data show that the highest incidence of 1-day maximum rainfall occurs in the IV quadrant or week 52 which is equal to 45.9%, in this case the highest number of flood events will occur when the sun moves towards the south. To identify heavy rain events that can cause flooding based on station rainfall data correlated with debits recorded on AWLR (Automatic Water Level Recorder). From the results of the identification that there was an increase in river discharge in November and December.
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Patandean, Candra Febryanto. "Analysis of Genesis Rain in Spring Transition in Makassar." Jurnal Ad'ministrare 6, no. 2 (February 4, 2020): 177. http://dx.doi.org/10.26858/ja.v6i2.12520.
Повний текст джерелаАнотація:
Extreme weather in this case heavy rains is common in the city of Makassar, both of which resulted in a flood or no flood. This type of research is descriptive research that aims to describe the incidence of rain in the transition season in Makassar. The source of data used in obtaining data on research in Makassar is secondary data. His research methods such as analysis method is based on monthly rainfall data to determine the monthly rainfall pattern using the Log Pearson III distribution methods and daily rainfall data duration of 3 hours early to analyze the frequency of rain by using Gumbel distribution methods. Based on the results in a graph of monthly rainfall patterns in the city of Makassar in the year (1985-2014) for 30 years and chart the frequency of daily rainfall duration 3 hours late in the year (2005 to 2014) for 10 years in the transition season in the city of Makassar, we can conclude that monthly rainfall patterns in Makassar is a monsoonal pattern with the second-largest peak intensity of rainfall occurs in January and December and the smallest intensity of rainfall occurs in August.
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Cecinati, Francesca, Antonio Moreno-Ródenas, Miguel Rico-Ramirez, Marie-claire ten Veldhuis, and Jeroen Langeveld. "Considering Rain Gauge Uncertainty Using Kriging for Uncertain Data." Atmosphere 9, no. 11 (November 14, 2018): 446. http://dx.doi.org/10.3390/atmos9110446.
Повний текст джерелаАнотація:
In urban hydrological models, rainfall is the main input and one of the main sources of uncertainty. To reach sufficient spatial coverage and resolution, the integration of several rainfall data sources, including rain gauges and weather radars, is often necessary. The uncertainty associated with rain gauge measurements is dependent on rainfall intensity and on the characteristics of the devices. Common spatial interpolation methods do not account for rain gauge uncertainty variability. Kriging for Uncertain Data (KUD) allows the handling of the uncertainty of each rain gauge independently, modelling space- and time-variant errors. The applications of KUD to rain gauge interpolation and radar-gauge rainfall merging are studied and compared. First, the methodology is studied with synthetic experiments, to evaluate its performance varying rain gauge density, accuracy and rainfall field characteristics. Subsequently, the method is applied to a case study in the Dommel catchment, the Netherlands, where high-quality automatic gauges are complemented by lower-quality tipping-bucket gauges and radar composites. The case study and the synthetic experiments show that considering measurement uncertainty in rain gauge interpolation usually improves rainfall estimations, given a sufficient rain gauge density. Considering measurement uncertainty in radar-gauge merging consistently improved the estimates in the tested cases, thanks to the additional spatial information of radar rainfall data but should still be used cautiously for convective events and low-density rain gauge networks.
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Ambildhuke, Geeta Mahadeo, and Barnali Gupta Banik. "Transfer Learning Approach - An Efficient Method to Predict Rainfall Based on Ground-Based Cloud Images." Ingénierie des systèmes d information 26, no. 4 (August 31, 2021): 345–56. http://dx.doi.org/10.18280/isi.260402.
Повний текст джерелаАнотація:
Clouds play a vital role in climate prediction. Rainfall prediction also majorly depends on the status and types of clouds present in the sky. Therefore, cloud identification is the most exciting and vital topic in meteorology and attracts most researchers from other areas. This paper presents the transfer learning technique to predict the Rainfall based on ground-based Cloud images responsible for rains. It will predict the estimated Rainfall by identifying the type of cloud by taking cloud images as input. The cloud images in the dataset are divided into three categories(classes) labeled as no-rain to very low-rain, low to medium-rain, and medium to high Rain based on the associated Precipitation responsible for the appropriate Rainfall. This model will be most helpful to the farmers to manage their Irrigation by knowing the status of Rainfall before every irrigation cycle or can also be helpful to take decisions on the outdoor events by taking prior knowledge of Rain. The model is trained on three classes to predict the Rainfall and firstly experimented with CNN. To improve the performance, the experiment is carried out with some best-pretrained models VGG16, Inception-V3, and XCeption using transfer learning and, the results are compared to the regular CNN model. The transfer learning technique is outperformed to get good accuracy as the dataset is too small and presented the best possible results of the model. Google colab with GPU setting makes the task fast and efficient to get the appropriate results in time, and performance achieved by transfer learning is excellent and can fulfill real-time requirements.
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Chen, Hai Xiu. "Design of Rain Sensor Based on Optical Principle." Applied Mechanics and Materials 668-669 (October 2014): 977–80. http://dx.doi.org/10.4028/www.scientific.net/amm.668-669.977.
Повний текст джерелаАнотація:
An optical rain sensor which can be used in automobile is described in this paper. The sensor is mainly composed of light source, light collimation system and light focusing system. When it rains, the rain sensor detects the rainfall on the automobile’s windshield surface through the light from the transmitter, and the light intensity received by the sensor receiver can be used to control the wiper to work automatically. The structure of the sensor is designed and the corresponding optical simulation is finished. With the optical rain sensor, the wiper device can work automatically and adjust the swing speed with the rainfall. The performance of automatic control of automobile and the driving safety are also improved.
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Madden, L. V., L. L. Wilson, and N. Ntahimpera. "Calibration and Evaluation of an Electronic Sensor for Rainfall Kinetic Energy." Phytopathology® 88, no. 9 (September 1998): 950–59. http://dx.doi.org/10.1094/phyto.1998.88.9.950.
Повний текст джерелаАнотація:
A novel sensor for measuring the kinetic energy of impacting raindrops, developed based on a soil-mass erosion sensor, was tested in the laboratory, with a rain simulator, and in the field. Drop impactions on the sensor—consisting of a piezoelectric crystal and associated electronics—produce an electrical charge that equals a fixed amount of energy. Calibration of the sensor was done in the laboratory using water drops of known diameter impacting with known velocity, and thus, with known kinetic energy. The relationship between pulse-count output of the sensor minus the background pulse counts when no drops were impacting (O; per min) and kinetic energy flux density (i.e., power [P; mJ cm-2 min-1]) was found to be described by the formula P; = (0.204 + 0.065 · O)0.67. The measurement threshold was 0.34 mJ cm-2 min-1. Using the sensor, generated rains with intensities of 23 to 48 mm/h were found to have powers of 0.4 to 2.2 mJ cm-2 min-1. In 2 years of field testing, 85 individual rain episodes were monitored, with mean intensities ranging from 0.1 to 42 mm/h. These rains had mean powers ranging from 0 to 5 mJ cm-2 min-1, and the highest power for a 5-min sampling period was 10 mJ cm-2 min-1. Both power and intensity varied greatly over time within rain episodes, and there was considerable variation in power at any given rain intensity, emphasizing the importance of measuring rather than simply predicting power. Although there was no known true power measurements for the generated or natural rains, estimates were realistic based on theoretical calculations, assuming that the gamma distribution represents raindrop sizes. The sensor is important in assessing the risk of rain splash dispersal of plant pathogens.
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Nishio, M., and M. Mori. "ANALYSIS OF DEBRIS FLOW DISASTER DUE TO HEAVY RAIN BY X-BAND MP RADAR DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 22, 2016): 125–32. http://dx.doi.org/10.5194/isprs-archives-xli-b8-125-2016.
Повний текст джерелаАнотація:
On August 20 of 2014, Hiroshima City (Japan) was struck by local heavy rain from an autumnal rain front. The resultant debris flow disaster claimed 75 victims and destroyed many buildings. From 1:30 am to 4:30 am on August 20, the accumulated rainfall in Hiroshima City exceeded 200 mm. Serious damage occurred in the Asakita and Asaminami wards of Hiroshima City. As a disaster prevention measure, local heavy rain (localized torrential rains) is usually observed by the Automated Meteorological Data Acquisition System (AMeDAS) operated by the Japan Meteorological Agency (JMA) and by the C-band radar operated by the Ministry of Land, Infrastructure, Transport and Tourism (MLIT) of Japan, with spatial resolutions of 2.5 km and 1 km, respectively. The new X-band MP radar system enables more detailed rainfall observations than the C-band radar. In fact, this radar can observe local rainfall throughout Japan in near-real time over a minimum mesh size of 250 m. A fine-scale accumulated rainfall monitoring system is crucial for disaster prevention, and potential disasters can be alerted by the hazard levels of the accumulated rainfall.
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Nishio, M., and M. Mori. "ANALYSIS OF DEBRIS FLOW DISASTER DUE TO HEAVY RAIN BY X-BAND MP RADAR DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 22, 2016): 125–32. http://dx.doi.org/10.5194/isprsarchives-xli-b8-125-2016.
Повний текст джерелаАнотація:
On August 20 of 2014, Hiroshima City (Japan) was struck by local heavy rain from an autumnal rain front. The resultant debris flow disaster claimed 75 victims and destroyed many buildings. From 1:30 am to 4:30 am on August 20, the accumulated rainfall in Hiroshima City exceeded 200 mm. Serious damage occurred in the Asakita and Asaminami wards of Hiroshima City. As a disaster prevention measure, local heavy rain (localized torrential rains) is usually observed by the Automated Meteorological Data Acquisition System (AMeDAS) operated by the Japan Meteorological Agency (JMA) and by the C-band radar operated by the Ministry of Land, Infrastructure, Transport and Tourism (MLIT) of Japan, with spatial resolutions of 2.5 km and 1 km, respectively. The new X-band MP radar system enables more detailed rainfall observations than the C-band radar. In fact, this radar can observe local rainfall throughout Japan in near-real time over a minimum mesh size of 250 m. A fine-scale accumulated rainfall monitoring system is crucial for disaster prevention, and potential disasters can be alerted by the hazard levels of the accumulated rainfall.
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Ayu, Srida Mitra, Andi Rosdayanti, and Eka Lolita. "THROUGHFALL PADA JABON MERAH (ANTHOCEPHALUS MACROPHYLLUS)." Jurnal Penelitian Kehutanan BONITA 2, no. 2 (December 28, 2020): 29. http://dx.doi.org/10.55285/bonita.v2i2.523.
Повний текст джерелаАнотація:
This study aims to measure the throughfall of Anthocepalus macrophyllu. The research was conducted in the experimental garden of SMK Neg 4 Luwu, Baramamase Village, Walenrang District, Luwu Regency. The materials used were 6 samples of Anthocephalus macrophyllus trees with a device consisting of a manual rainfall gauge, a hose, a collection bucket, a measuring cup, nails, machetes and a stopwatch. The data collected were rainfall and rainfall at 30 rain events. Of the 30 rainfall events, the throughfall data were selected for rainfall of 100, 150, 300, 400 and 500 cm3, each with 3 replications. Rainfall data is obtained by placing a manual rain gauge at the research location to measure every time it rains. Throughfall measurement is done by placing the collection bucket on the inside under the canopy. The highest average throughfall of 42.67 cm3 is found in the 500 cm3 rainfall with the regression equation y = 0.086x + 1.202 and determination (R2) = 0.8099. While the largest proportion of throughfall with a value of 13.05% occurs in 300 cm3 of rainfall, the regression equation y = 0.0022x + 8.186 and determination (R²) = 0.0247
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Hambali, Roby, Djoko Legono, Rachmad Jayadi, and Satoru Oishi. "Improving Spatial Rainfall Estimates at Mt. Merapi Area Using Radar-Rain Gauge Conditional Merging." Journal of Disaster Research 14, no. 1 (February 1, 2019): 69–79. http://dx.doi.org/10.20965/jdr.2019.p0069.
Повний текст джерелаАнотація:
Rainfall monitoring is important for providing early warning of lahar flow around Mt. Merapi. The X-band multi-parameter radar developed to support these warning systems provides rainfall information with high spatial and temporal resolution. However, this method underestimates the rainfall compared with rain gauge measurements. Herein, we performed conditional radar-rain gauge merging to obtain the optimal rainfall value distribution. By using the cokriging interpolation method, kriged gauge rainfall, and kriged radar rainfall data were obtained, which were then combined with radar rainfall data to yield the adjusted spatial rainfall. Radar-rain gauge conditional merging with cokriging interpolation provided reasonably well-adjusted spatial rainfall pattern.