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This paper presents the correlation analysis between lightning flashes and the rainfall rate of a thunderstorm when a flash flood event happened in Melaka on 11 August 2020. Four types of data have been collected from the electric field mill (EFM), fast antenna (FA) system, constant altitude plan position indicator (CAPPI) radar and world wide lightning location network (WWLLN). Two storms have been detected by the EFM occurred between 04:00:00 and 14:00:00. The FA system recorded a total of 33 lightning flashes had detected with the highest number occurrence of flashes which positive narrow bipolar event (+NBE) around 21 flashes, the maximum rainfall rate and reflectivity have been detected by radar during the first storm were 8 mm h-1 and 37 dBZ, respectively (light rain). During the second storm, there was a total of 980 lightning flashes detected by the FA system with the highest number occurrence of flashes around 429 flashes (IC), the highest value of rainfall rate and reflectivity is 50 mm h-1 and 50 dBZ, respectively (heavy rain). Analyses of the lightning and rainfall rate data also show a close link between the occurrence of major thunderstorms systems and flash flooding on a regional scale.

In this paper, the effect of heavy rainfall on the propagation of a 38-GHz in a tropical region was studied and analyzed. Real measurement was collected, with a path length of 300 meters, for a (5G) radio linkage in Malaysia, installed at the Universiti Teknologi Malaysia (UTM) Johor Bahru campus. The employed system entails an Ericsson MINI-Link 38 E-0.6 mm, with a horizontal polarization (HP) antenna at the top integrated with a rain gauge and a data logger. Daily registered samples with a single minute span, for a full study period of 1 month, were collected and evaluated. The obtained rain rate was found as 56 mm/hr with a specific rain attenuation of 18.4 dB/km for 0.01% of the time. In addition to that, a calculated average rain attenuation of 5.5 dB for the transmission path of 300 meters length, was calculated. Based on these findings, a recommendation to update the International Telecommunication Union (ITU) specification of the rain attenuation for Malaysia is proposed. Based on the results, we suggest shifting the zone classification of Malaysia from zone P to zone N-P. Therefore, accurate design for future 5G systems would rely on more precise estimated attenuation levels leading to enhanced performance.

This paper investigates the performance of different ITU models in predicting Malaysia s tropical rainfall rates and rain attenuation. This investigation is considered at 26GHz mm-wave frequency, and three datasets collected at different regions in Malaysia with emphasize on the latest dataset in Skudai in 2012. The data collected has rainfall rate and rain attenuation measurements for a continuous year at 1 spm sampling rate. Nonlinear regression is used to estimate best fit parameters for comparison with ITU-R p.837-1 with rain zone data, ITU-R p.837-6 as method 1 and ITU-R p.837-7 as method 2. Results show that ITU method 2 outperforms all the models with RMSE in the range of 12.72 mm/hr and 3.51 dB/km for rainfall rate and rain attenuation respectively. Conversely, absolute error at 0.01% of time showed superiority of ITU-R p.837-1 tropical recommendation with absolute error in the range of 0.39 mm/hr and 4.16 dB/km for rainfall rate and rain attenuation respectively. All models showed significant deviation from the measurements and the best fit at lower than 0.01% of time, with minimum deviation observed for of ITU method 2 in that range. Worst month parameters estimation using ITU method2 is in good match to the best fit estimation.

In this study, we investigated the impact of rainfall rate and temperature during fruit development on chilling injury (CI) of Queen pineapples (Ananas comosus L. Merr) after cold storage at 13 °C. The pineapples were induced to flower in October 2016 and May 2017. Rainfall and field temperature during fruit development were recorded. The fruit were harvested in March 2017 and October 2017 (135 d after anthesis), respectively. Visual appearance, CI score, lightness (L*) value, parameters related to membrane integrity, and the activities of enzymes related to browning of the tissue adjacent to the core were monitored in the fruit after 7 and 14 d of cold storage followed by room temperature storage (27 ± 1 °C) (RT) for 2 d. High CI incidence was associated with high rainfall rather than the field temperature (approx. 27–29 °C) during fruit development. The fruit harvested in March experienced higher rainfall during fruit development than the fruit harvested in October. The CI severity of the fruit harvested in March was greater than that of fruit harvested in October. The higher CI severity of the fruit harvested in March was accompanied with reduced membrane integrity as well as enzymatic browning compared to the fruit harvested in October. In conclusion, high rainfall during fruit development is a major factor for CI of Queen pineapple grown in tropical zones. The results of this investigation provide insight into the causes underlying the loss of fruit quality during storage and marketing.

Agriculture is one of the main economic activities in the Peruvian Andes; rainwater alone irrigates more than 80% of the fields used for agriculture purposes. However, the cloud and rain generation mechanisms in the Andes still remain mostly unknown. In early 2014, the Instituto Geofísico del Perú (IGP) decided to intensify studies in the central Andes to better understand cloud microphysics; the Atmospheric Microphysics And Radiation Laboratory officially started operations in 2015 at IGP’s Huancayo Observatory. In this work, a Ka-band cloud profiler [cloud and precipitation profiler (MIRA-35c)], a UHF wind profiler [Clear-Air and Rainfall Estimation (CLAIRE)], and a VHF wind profiler [Boundary Layer and Tropospheric Radar (BLTR)] are used to estimate rainfall rate at different conditions. The height dependence of the drop size diameter versus the terminal velocity, obtained by the radars, in the central Andes (3350 m MSL) was evaluated. The estimates of rainfall rate are validated to ground measurements through a disdrometer [second-generation Particle, Size, and Velocity (PARSIVEL2)] and two rain gauges. The biases in the cumulative rainfall totals for the PARSIVEL2, MIRA-35c, and CLAIRE were 18%, 23%, and −32%, respectively, and their respective absolute biases were 19%, 36%, and 63%. These results suggest that a real-time calibration of the radars, MIRA-35c and CLAIRE, is necessary for better estimation of precipitation at the ground. They also show that the correction of the raindrop terminal fall velocity, obtained by separating the vertical wind velocity (BLTR), used in the estimation the raindrop diameter is not sufficient, especially in convective conditions.

Typhoon Bolaven caused significant damage with severe rainfall all over South Korea, including Cheju Island, which received more than 250 mm in 2 days in August 2012. It was regarded as the most powerful storm to strike the Korean Peninsula in nearly a decade. The rainfall-rate datasets were obtained from S-band radar operated by the Korea Meteorological Administration to be analyzed and compared with the mesoscale Cloud Resolving Storm Simulator (CReSS) model simulation. Multifractal analysis was conducted to understand the structure of the rainfall rate with height in the typhoon system. The radar rainfall data presented with strong intermittency across scales at lower altitudes (1 and 2 km) and a more homogeneous rainfall field at high altitude (5 km) with two parameters (fractal codimension and multifractality index). The statistical scaling moment function and maximal singularities show clear significant differences between radar and the CReSS model.

Effective rain rate estimation using satellite-based measurement is imperative for many hydro-meteorological applications. With the recent advancement in satellite products and retrieving algorithm...

this paper comparing the the performance of different ITU-837 in predicting malaysias' rain attenuation CCDF.

this paper comparing the the performance of different ITU-837 in predicting malaysias' rain attenuation CCDF.

Rain gauge measurement represents only point rainfall and considered as the “Ground truth” for rainfall rate, but it is associated with different errors and exposed to outliers. On the other hand radar does not directly measure rainfall rates, but it estimates rainfall rate, R (mm/h) by an empirical relationship with the radar reflectivity factor, Z (mm6/m3). Reflectivity is converted into a rainfall rate by the Z-R relationship using the formula: Z = aRb and we determine both of the coefficients (with 95% confidence bounds) , and For Bahir Dar station- I, Bahir Dar station-II and the overall station respectively.

This contribution describes a realistic rain model that considers a cluster of axis-symmetric but flattened raindrops with a specified shape–size relation, a raindrop size distribution, and a distribution of orientation angle of the symmetry axis. The backscattering cross section and specific attenuation due to the rain medium are determined by the extended boundary condition method. The model is applied to data from two X-band radars to estimate reflectivity and rainfall rate, considering attenuation effects during the two-way propagation between the radar and each sampled rain volume. The results are then compared with corresponding ones from well-established attenuation-correction methods. One of these methods, which relies on unattenuated reflectivities measured by an S-band radar, has been carefully validated by a previous study. The reasonable agreement between the two methods indicates that the proposed model may be a suitable option to estimate reflectivity and rainfall rate fields based on X-band radar data, particularly when no such references are available.

Comparative study of the performance of different ITU model in predicting Malaysia tropical climate properties.

A propagation campaign of attenuation measurements with the 40-GHz Alphasat beacon signal is being conducted at the Universidad Politecnica de Madrid (UPM). Besides attenuation, rainfall rate data are collected with a rain gauge and a disdrometer. Rainfall rate and attenuation statistics can be used for assessment and development of attenuation prediction models for satellite radio links. In this paper, the results obtained from 5 years of rainfall rate and attenuation measurements are presented and compared with several relevant propagation models: the ITU-R P.837-6, ITU-R P.837-7 and MORSE models for rainfall rate and the ITU-R P.618-13 for attenuation. A moderate accuracy has been achieved with all models. The ITU-R P.837-7 and MORSE models improve the prediction for probabilities lower than approximately 0.01%, whereas for higher probabilities the three models show a similar performance.

A realistic approach for gathering high-resolution observations of the rainfall rate, R, in the vertical plane is to use data from vertically pointing Doppler radars. After accounting for the vertical air velocity and attenuation, it is possible to determine the fine, spatially resolved drop size spectra and to calculate R for further statistical analyses. The first such results in a vertical plane are reported here. Specifically, we present results using MRR-Pro Doppler radar observations at resolutions of ten meters in height over the lowest 1.28 km, as well as ten seconds in time, over four sets of observations using two different radars at different locations. Both the correlation functions and power spectra are useful for translating observations and numerical model outputs of R from one scale down to other scales that may be more appropriate for particular applications, such as flood warnings and soil erosion, for example. However, it was found in all cases that, while locally applicable radial power spectra could be calculated, because of statistical heterogeneity most of the power spectra lost all generality, and proper correlation functions could not be computed in general except for one 17-min interval. Nevertheless, these results are still useful since they can be combined to develop catalogs of power spectra over different meteorological conditions and in different climatological settings and locations. Furthermore, even with the limitations of these data, this approach is being used to gain a deeper understanding of rainfall to be reported in a forthcoming paper.

Corona onset voltage gradient (COG) of bundled conductors is an important factor to be considered when designing extra-high voltage (EHV) and ultra-high voltage (UHV) transmission lines. For alternating current (AC) transmission lines, the electromagnetic environment degrades and the energy loss is greater on rainy days, which becomes more obvious with increasing altitude, therefore, it is particularly important to investigate corona onset characteristics of bundled conductors under rainy conditions in high-altitude areas. Based on an UHV corona cage established in Qinghai Province, China at an altitude of 2200 m, corona onset characteristics of nine types of bundled conductors generally used in EHV and UHV AC transmission lines were measured at a rainfall rate of up to 15 mm/h. Moreover, COG was obtained by using the tangent method. Changes in COG with rainfall intensity and corona characteristics with structural parameters of conductors at the saturated rainfall rate were investigated. Finally, considering sub-conductor radius, the number of sub-conductors, and rainfall rate, an empirical prediction equation for COG of bundled conductors with 4, 6 and 8 sub-conductors and cross-sectional areas of 400, 500, 630, and 720 mm2 was proposed, which could provide a reference for the design of overhead transmission lines in high-altitude areas.

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 &ge, 80%. The power-law R-k relationships between rain-induced specific attenuation, k (dB km&minus, 1), and the rainfall rate, R (mm h&minus, 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 &minus, 3 and 1 mm h&minus, 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.

One-minute rain rate exceeded for 0.01% of an average year (known as R0.01) is an important parameter, which is required in rain fade models for planning both satellite and terrestrial links, especially in the microwave and millimeter-wave bands. This paper presents the development of a new global model for estimating high-resolution R0.01. The model is developed using the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS), ERA-Interim reanalyzed total precipitable water, and the cumulative distribution functions of the measured R0.01 via genetic algorithm. The newly proposed model performs better than the International Telecommunication Union Radio Sector (ITU-R) recommendation and widely used ITU-R P.837-6 model, particularly over the tropical regions, where ITU-R P.837-6 strongly underestimates R0.01. Overall, when compared to ITU-R P.837-6, the estimated R0.01 by the proposed model is improved by ~15%. Furthermore, the proposed model can provide R0.01 with a much higher spatial resolution (~5 km) as compared to ITU-R P.837-6 (~110 km). Another key advantage of the proposed model over ITU-R P.837-6 is that the inputs required for this model are readily available from meteorological database as well as from space-based observing system. This paper also investigated the long-term (1981–2016) trends in R0.01. The analysis revealed significant increasing trends in R0.01 over most parts of the globe, India and northern part of Southern America exhibited the strongest ( $\sim 0.5\,\,\text {mm}\cdot \text {h}^{-1}\cdot $ year−1) increasing trends. It is anticipated that R0.01 obtained with the newly proposed model will have large implications in rain attenuation modeling for planning both terrestrial and earth–satellite microwave links.

The Convolutional Neural Network Model (CNN) has shown excellent performance in many tasks in recent years, such as the application in image recognition and classification. In this paper we propose a method based on the deep convolutional neural network model VGG and radar reflectivity factor to quantitatively estimation the rainfall rate intensity, which improves the shortcomings of the traditional method Z-R relationship with high error. We selected the shallow convolutional neural network LeNet for comparison. Then, we studied the effect of selecting different sizes of radar reflectivity factor images on the quantitative estimation of rainfall rate intensity. The results show that the depth convolutional neural network VGG and the relatively large size of radar reflectivity factor image are better than the traditional Z-R relationship and shallow convolutional neural network LeNet.

Method for rainfall rate estimation with satellite based microwave radiometer data is proposed. A method to consider the geometric relationship of the observed ice particles and microwave radiometer in the estimation of precipitation is shown, and its validity is shown by comparing it with precipitation radar data on the ground. Observations at high altitudes, such as ice particles, differ greatly in the location of the observation point projected on the ground surface and in the upper troposphere where the observations exist. This effect was insignificant when the precipitation was small because ice particles were often absent, but it was found that the effect was large when the precipitation was large. In other words, the proposed method is effective and effective for Advanced Microwave Scanning Radiometer (AMSR) data in Houston, which was shown as an example of a highly developed convective rain cloud with an In the case of Kwajalein, the effect is insignificant. In addition, the proposed method requires an assumption of ice particle height, and it is necessary to make assumptions based on climatic values. In addition, microwaves in the 89 GHz band, which are considered to be sensitive to ice particles, are not only sensitive to ice particles, so it must be taken into account that they are also affected by the presence of non-ice particles.

Radio waves especially at the millimeter-wave band are known to be attenuated by rain. Radio engineers and designers need to be able to predict the time of the day when radio signal will be attenuated so as to provide measures to mitigate this effect. This is achieved by characterizing the rainfall intensity for a particular region of interest into worst month and worst hour of the day. This paper characterized rainfall in Nigeria into worst year, worst month, and worst hour. It is shown that for the period of study, 2008 and 2009 are the worst years, while September is the most frequent worst month in most of the stations. The evening time (LT) is the worst hours of the day in virtually all the stations.

An analysis based on rainfall rate characteristics has been carried out to estimate flood occurance. In this paper, we analyzed the rain gauge data for 5 different rain gauge stations. 14 days acquired data covering events before, during and after the flood tragedy in Malaysia. The analysis of the rain gauge data was processed on precipitation phenomena observed in year 2014 in Kota Bharu, Kelantan (Malaysia) from 13 December until 26 December. The data was acquired from the Malaysian Drainage and Irrigation Department (DID). The objective of the research is to derive the tropical flood estimation model using rain gauge data in Malaysia. Among the preliminary result shows that the average rainfall rate at kota bharu is 204.5 mm/hr during the flood tragedy

The National Oceanic and Atmospheric Administration (NOAA) Geostationary Operational Environmental Satellite series R (GOES-R) will greatly expand the ability to observe the earth from geostationary orbit compared to the current-generation GOES, with more than 3 times as many spectral bands and a 75% reduction in footprint size. These enhanced capabilities are beneficial to rainfall rate estimation since they provide sensitivity to cloud-top properties such as phase and particle size that cannot be achieved using the limited channel selection of current GOES. The GOES-R rainfall rate algorithm, which is an infrared-based algorithm calibrated in real time against passive microwave rain rates, has been previously described in an algorithm theoretical basis document (ATBD); this paper describes modifications since the release of the ATBD, including a correction for evaporation of precipitation in dry regions and improved calibration updates. These improvements have been evaluated using a simplified version applicable to current-generation GOES to take advantage of the high-resolution ground validation data routinely available over the conterminous United States. Correcting for subcloud evaporation using relative humidity from a numerical model reduced false alarm rainfall by half and reduced the overall error by 35% for hourly accumulations validated against the National Centers for Environmental Prediction stage IV radar–gauge field; however, the number of missed events did increase slightly. Reducing the size of the calibration regions and increasing the training data requirements improved the consistency of the retrieved rates in time and space and reduced the overall error by an additional 4%.

The knowledge of adequate rainfall statistics will contribute greatly to the roll-out of emerging wireless technologies on the platform of Long-Term Evolution (LTE) and WiMax (IEEE 802.16). Therefore, it is important that rainfall measurements at shorter integration time are incorporated as useful inputs in the planning of Line-of-Sight (LOS) microwave and millimetre communication links for hosting these technologies. As compared to the use of one-minute rainfall data as suggested by International Telecommunication Union (ITU), the equivalent data measured at 30-second interval gives more information of temporal rain rates in the time domain. Therefore, in this study, rainfall rate measurements of 5-minute integration time representative of 10 locations in South Africa are evaluated to obtain their cumulative distributions. Results from these analyses are compared with rainfall data of one-minute and 30-second integration time data obtained over Durban (29°52'E, 30°55'S), South Africa. Consequently, rainfall rate models for conversion to one-minute and 30-second integration times were obtained over 10 locations in South Africa using the power-law regression functions. Our results obtained over these locations were used to estimate specific attenuation values in selected microwave and millimetric wave bands at 12 GHz, 30 GHz and 60 GHz for 10 locations under study. It is confirmed that the 30-second integration time provides more information needed for estimation of specific attenuation on microwave and millimeter-wave radio links in South Africa.

187 p. Due to the need for an understanding of the rain structure and the effect of rainfall on the high frequency wireless communication links, several issues related to the characters of rainfall rates and rain attenuation in Singapore are studied. This will enable the development of a comprehensive rain attenuation model. MASTER OF ENGINEERING (EEE)

The convective rainfall rate from cloud physical properties (CRPh) algorithm for Meteosat second-generation satellites is a day-only precipitation algorithm developed at the Spanish Meteorological Agency (AEMET) for EUMETSAT’ Satellite Application Facility in support of nowcasting and very short-range forecasting (NWC SAF). It is therefore mainly intended to provide input for monitoring and near-real-time forecasts for a few hours. This letter critically discusses the theoretical basis of the algorithm with special emphasis on the empirical values and assumptions in the microphysics of precipitation, and compares the qualitative performances of the CRPh with its antecessor, the convective rainfall rate algorithm (CRR), using an object-based method applied to a case-study. The analyses show that AEMET’s CRPh is physically consistent and outperforms the CRR. The applicability of the algorithm for nowcasting and the challenges of improving the product to an all-day algorithm are also presented.

Communication via satellite is still one of the most important choices in telecommunication especially for areas which are not covered by optical fiber networks. However, the radio frequency used in communication satellites is affected by rain attenuation, which is called as rain attenuation. The rain attenuation increases with increasing rainfall rate and operating frequency. Therefore, accurate estimation of 1-min rainfall rate is important for modelling rain attenuation. However, in the tropics such as Indonesia, precipitation varies in several time scales. Furthermore, climate change has increased the frequency of occurrence of extreme rain and this condition may also affect the communication system. The ITU-R model which is widely used to estimate rain attenuation assumes a stationary climate. This research analysed rainfall pattern in Indonesia. In addition, the variation in melting layer height was also investigated. The rain gauge observation in some locations in Indonesia, i.e., Kototabang, Pontianak, Manado and Biak, were analyzed. The rainfall pattern was analysed using wavelet transforms. In addition, the percentage of time exceeded of several rainfall rate which are commonly used in modeling and design of telecommunication systems was also discussed. For melting layer height, 17 years of the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data particularly TRMM PR 2A25 version 7 data were used. A 128–256 days scale band oscillation (seasonal) is observed at Kototabang, Pontianak and Biak, but it is not observed at Manado. This seasonal oscillation is an interval-independent characteristic, indicating a stationary dynamic of this signal. Intrasesonal oscillation is an interval-dependent characteristic in which the period of oscillation is not constant indicating a nonstationary dynamic of this signal. At Manado, Pontianak and Kototabang, 256–512 days scale band oscillation is also observed, but it is not clearly observed at Biak. It was also found that there is an increase of rainfall rate for small percentage of time exceeded. Furthermore, there is a slight increase of melting layer height at Kototabang, Pontianak and Biak. In Manado, linear regression shows a decrease of melting layer height with the increase of year.

A fixed Z-R relationship approach, such as the Marshall-Palmer relationship, for an entire year and for different seasons can be problematic in cases where the relationship varies spatially and temporally throughout a region. From this perspective, this study explores the use of a long-term radar reflectivity factor for South Korea to obtain a nationwide calibrated power law relationship, Z = α ∙ R β , where R is the rainfall intensity and Z is the reflectivity factor, in the context of bias-correction and the associated uncertainties within a Bayesian regression framework. This study also investigates seasonal differences in the bias-correction parameters (i.e., additive and multiplicative bias-correction factors) and their roles in reducing systematic error. Distinct differences in the calibrated parameters over stations are identified, and more importantly, an inverse relationship between the two reflectivity parameters α and β (i.e., decreasing trend in β with increasing α ) is clearly identified with different parameter space based on the seasons. A spatially structured pattern in the parameters exists, particularly parameter α, for the wet season and parameter β for the dry season. A pronounced region of high values in the power law parameters (i.e., α and β) during the wet and dry seasons may be partially due to the overestimation of the radar reflectivity factor associated with enhancement of moisture transport directly over the coastal region. Finally, the radar rainfall estimates through the calibrated Z-R relationship are compared with the currently used Z-R relationships for estimating stratiform rainfall and convective rainfall. Overall, the radar rainfall fields based on the proposed modeling procedure are similar to the observed rainfall fields, whereas the radar rainfall fields obtained from the currently used Marshall-Palmer Z-R relationship show a systematic underestimation. The calibrated Z-R relationships are further validated by testing the predictions of unseen radar-gauge pairs in the year 2018, in the context of cross-validation. The cross-validation results are largely similar to those in the calibration process, suggesting that the derived Z-R relationships fit the radar-gauge pairs reasonably well.

Distributions of drop sizes can be expressed as DSD = Nt × PSD, where Nt is the total number of drops in a sample and PSD is the frequency distribution of drop diameters (D). Their discovery permitted remote sensing techniques for rainfall estimation using radars and satellites measuring over large domains of several kilometers. Because these techniques depend heavily on higher moments of the PSD, there has been a bias toward attributing the variability of the intrinsic rainfall rates R over areas (σR) to the variability of the PSDs. While this variability does increase up to a point with increasing domain dimension L, the variability of the rainfall rate R also depends upon the variability in the total number of drops Nt. We show that while the importance of PSDs looms large for small domains used in past studies, it is the variability of Nt that dominates the variability of R as L increases to 1 km and beyond. The PSDs contribute to the variability of R through the relative dispersion of χ = D3Vt, where Vt is the terminal fall speed of drops of diameter D. However, the variability of χ is inherently limited because drop sizes and fall speeds are physically limited. In contrast, it is shown that the variance of Nt continuously increases as the domain expands for physical reasons explained below. Over domains larger than around 1 km, it is shown that Nt dominates the variance of the rainfall rate with increasing L regardless of the PSD.

The microwave radio links above 5 GHz suffer from attenuation due to precipitation. The need for employing higher frequencies has therefore encouraged research into rain attenuation due to precipitation. The natural variations of tropical precipitation occur in a wide range of time-scales, so does probably the behavior of radio communication links. This paper examines the variations of cumulative distribution of rainfall in Sumatra from an optical rain gauge measurement with a near continuous record of operation over eleven consecutive years (2002-2012). The worst month statistics were also examined and all results were compared with the ITU-R model. Of some natural variations of rainfall rate investigated, the diurnal variation had the most significant effect on the cumulative distribution of rainfall rate. The ITU-R model overestimated the rainfall rate for the first half of the day (00:00-11:59 LT) whereas it underestimated the rainfall rate until 0.01% of time for the second half of the day (12:00-23:59 LT) before the model starts to overestimate. The ITU model overestimated 52.85% of rainfall rate at 0.01% of time for the first half of the day and underestimates 7.59% for the second half. Considerable differences between the recorded data and the ITU-R model for the annual, seasonal, and intreaseasonal variations are only significant at small time percentage (≤ 0.01%). The relationship of worst month statistics was also slightly different from the ITU-R model. This result reinforces the previous studies on the limitation of the ITU-R model for the tropical region.

This paper proposes appropriate locations for site diversity to provide stable satellite communication service in Korea. For this pur-pose, we analyzed rainfall rate data measured by KMA for 5 years at 88 sites, and the variations of simultaneous occurrence of rainfall rate in pairs of sites using the correlation coefficient. This paper provided contour maps of the spatial ditstribution of rainfall rate corre-lation, and proposed information on the optimum sites/regions for the operation of muti-uplink satellite systems, in 4 cities which were principal in field of satellite communication in Korea.Key words: Site Diversity, Satellite Communication, Rainfall Rate, Correlation Coefficient, Correlation Map  Q“)”0•(Technical Regulation Division, National Radio Research Agency) xManuscript received September 8, 2015 ; Revised October 19, 2015 ; Accepted November 9, 2015. (ID No. 20150908-066)xCorresponding Author: Yong-Ki Kwon (e-mail: ygkwon@msip.go.kr) ⓒ Copyright The Korean Institute of Electromagnetic Engineering and Science. All Rights Reserved.

Rain attenuation is the main impairment for radio communication systems operating at frequencies above 10GHz, and the rainfall rate data exceeded for 0.01% of the average year are the essential data for rain attenuation prediction. Three kinds of digital maps of rain rate (mm/h) exceeded for 0.01% of the average year in China land area have been compared and analyzed herein, which are the methods in Recommendation ITU-R P.837-7, P.837-4, and the grid data produced by using the statistical data in widely distributed station in China land area. The comparison shows that the method in P.837-7 is better than previous ITU-R method, but there are still many differences between the method in P.837-7 and the grid map obtained by the local data sources in China land area.

The constant development of science and technology in weather radar results in high-resolution spatial and temporal rainfall estimates and improved early warnings of meteorological phenomena such as flood [1]. Weather radars do not measure the rainfall amount directly, so a relationship between the reflectivity (Z) and rainfall rate (R), called the Z-R relationship (Z = aRb), where a and b are empirical constants, can be used to estimate the rainfall amount. In this research, mathematical techniques were used to find the best climatological Z-R relationships for the Low Coastal Plain of Guyana. The reflectivity data from the S-Band Doppler Weather Radar for February 17 and 21, 2011 and May 8, 2012 together with the daily rainfall depths at 29 rainfall stations located within a 150 km radius were investigated. A climatological Z-R relationship type Z = 200R1.6 (Marshall-Palmer) configured by default into the radar system was used to investigate the correlation between the radar reflectivity and the rainfall by gauges. The same data sets were used with two distinct experimental Z-R relationships, Z = 300R1.4 (WSR-88D Convective) and Z = 250R1.2 (Rosenfeld Tropical) to determine if any could be applicable for area of study. By comprehensive regression analysis, New Z-R and R-Z relationships for each of the three events aforementioned were developed. In addition, a combination of all the samples for all three events were used to produce another relationship called “All in One”. Statistical measures were then applied to detect BIAS and Error STD in order to produce more evidence-based results. It is proven that different Z-R relationships could be calibrated into the radar system to provide more accurate rainfall estimation.

In this paper, we present a model for rainfall rate prediction 30 seconds ahead of time using an artificial neural network. The resultant predicted rainfall rate can then be used in determining an appropriate fade counter-measure, for instance, digital modulation scheme ahead of time, to keep the bit error rate (BER) on the link within acceptable levels to allow constant flow of data on the link during a rain event. The approach used in this paper is pattern recognition technique that considers historical rainfall rate patterns over Durban (29.8587°S, 31.0218°E). The resultant prediction model is found to predict an immediate future rain rate when given three adjacent historical rain rates. For our model validation, error analysis via root mean square (RMSE) technique on our prediction model results show that resultant errors lie within acceptable values at different rain events within different rainfall regimes.

The performance of both a recent rainfall rate model and the inter-annual variability prediction method proposed by the International Telecommunication Union has been assessed taking advantage of the availability of 16 years of rain gauge data. The above rainfall rate model produces as well monthly rainfall rate distributions that have been compared with the experimental monthly distributions achieving good results. The procedure proposed in the ITU variability prediction method has been adapted to test its usefulness to estimate monthly and seasonal variability. In some cases, fair agreement has been found between estimated and experimental variability.

The scattering and absorption of communication signal propagated through the troposphere by rainfall is a major cause for attenuation. For a proper mitigation of this impairment, an adequate understanding of rain rate must be carried out. Hence a 6-years of one-minute rain rate and four years measurement at Ota, Southwest, Nigeria (6° 42N, 3° 14E), using a wireless Davis Vantage Pro2 Weather Station is presented. The rainfall rate data span from April 2012 to December 2015 has been analysed. One-minute rainfall rate is required for the prediction and modelling of rain attenuation at microwave frequencies for a region like the Nigeria at various percentage of time. International Telecommunication Union – Recommendation (ITU-R) divided the world into rainfall zones of which Nigeria falls into the P zone. However, the maximum rainfall rate at 0.01% of time in the P zone is 145 mm/hr of which Ota is overestimated. The measured yearly averaged maximum one-minute rainfall rate for 2012, 2013, 2014, 2015, 2016 and 2017 are 157.7 mm/h, 148.0 mm/h, 241.2 mm/h, 157.3 mm/h, 140.6 mm/h and 250.8 mm/h respectively.

The convective rainfall rate from cloud physical properties (CRPh) algorithm for Meteosat second-generation satellites is a day-only precipitation algorithm developed at the Spanish Meteorological Agency (AEMET) for EUMETSAT’ Satellite Application Facility in support of nowcasting and very short-range forecasting (NWC SAF). It is therefore mainly intended to provide input for monitoring and near-real-time forecasts for a few hours. This letter critically discusses the theoretical basis of the algorithm with special emphasis on the empirical values and assumptions in the microphysics of precipitation, and compares the qualitative performances of the CRPh with its antecessor, the convective rainfall rate algorithm (CRR), using an object-based method applied to a case-study. The analyses show that AEMET’s CRPh is physically consistent and outperforms the CRR. The applicability of the algorithm for nowcasting and the challenges of improving the product to an all-day algorithm are also presented.