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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.

In Japan, there are many natural disasters that often expose residents to the risk of serious damage. To minimize such damage, the Japanese government has built a disaster information network using a radio system, and as part of it, an outdoor acoustic mass notification system is routinely operated. However, its intelligibility may be reduced by outdoor noise, which is increased by rainfall. In the present study, long-term surveys of rainfall rate and outdoor noise were conducted at four sites with different surrounding environments and the relationship between them was analyzed to clarify the effects of the rainfall rate on the physical characteristics of outdoor noise. The results indicated that the median sound pressure level for each 1/3 octave band increased with increasing rainfall rate, mainly above mid-frequencies of around 500 Hz to 1 kHz, though the frequency at which the level began to rise depended on the time period and site. Furthermore, a newly proposed macroscopic model for estimating the sound pressure level of outdoor noise under rainy conditions indicated that the distance from the loudspeaker of the system to ensure a certain speech-to-noise ratio could be significantly reduced by heavy rainfall.

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.

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.

YNA DOI: https://doi.org/10.15446/dyna.v86n209.73774 DYNA, Volumen 86, Número 209, p. 30-39, 2019. ISSN electrónico 2346-2183. ISSN impreso 0012-7353. Rainfall rate and rain attenuation contour maps for preliminary “Simon Bolivar” satellite links planning in Venezuela Mapas de contorno de tasa de precipitación y atenuación por lluvias para planificación preliminar de enlaces del satélite "Simón Bolívar" en Venezuela Angel Dario Pinto Mangones, Nelson Alexander Pérez García, Juan Manuel Torres Tovio, Eduardo José Ramírez, Samir Oswaldo Castaño Rivera, Jaime Velez Zapata, John Dwiht Ferreira Rodríguez, Leidy Marian Rujano Molina Texto completo: PDF (English) Bookmark and Share Resumen (en_US) Predicting precipitation rate and rainfall attenuation are key aspects in planning and dimensioning of wireless communications systems operating at frequencies above 10 GHz, such as satellite communication systems at Ku and Ka bands. In this paper, contour maps of rainfall rate and rain attenuation are developed for the first time in Venezuela, based on 1-min rain rate statistics obtained from measurements carried out in Venezuela over at least 30 years period with a higher integration time and using Rice-Holmberg model, refined Moupfouma-Martin model and Recommendation ITU-R P.837-7, for rain rate estimation and Recommendation ITU-R P.618-13, Ramachandran-Kumar model, Yeo-Lee-Ong model and Rakshit-Adhikari-Maitra model, for rain attenuation prediction in “Simon Bolivar” satellite links in Venezuela. The overall results of both types of maps represent a useful tool for preliminary planning of those links in the country, specifically, in Ku and Ka bands. La tasa de precipitación y la atenuación por lluvias son aspectos claves en la planificación y dimensionamiento de sistemas inalámbricos de comunicaciones que operan en frecuencias superiores a 10 GHz, tales como los sistemas de comunicación vía satélite en las bandas Ku y Ka. En este artículo, se desarrollan por primera vez en Venezuela mapas de contorno de tasa de precipitación y atenuación por lluvias, en base a estadísticas de lluvia de 1-minuto obtenidas a partir de mediciones realizadas en Venezuela en un periodo de al menos 30 años con alto tiempo de integración y usando los modelos Rice-Holmberg, Moupfouma-Martin refinado y Recomendación ITU-R P.837-7, para la estimación de la precipitación y los modelos Recomendación ITU-R P.618-13, Ramachandran-Kumar, Yeo-Lee-Ong y Rakshit-Adhikari-Maitra, para la predicción de la atenuación por lluvias para enlaces del satélite “Simón Bolívar” en Venezuela. Los resultados generales de ambos tipos de mapas representan una herramienta útil para la planificación preliminar de dichos enlaces en el país, específicamente, en las bandas Ku y Ka.

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 prediction of rainfall rate characteristics at small space-time scales is currently an important topic, particularly within the context of the planning and design of satellite network systems. A new comprehensive interpolation approach is presented in this paper to deal with such an issue. There are three novelties in the proposed approach: (1) the proposed interpolation approach is not directly applied to measured rain precipitation (either radar or raingauge-derived data) but focuses on the coefficients of the fitted statistical distributions and/or computed rain characteristics at each location; (2) the parameter databases are provided and the contour maps of coefficients spanning Western Europe have been created. It conveniently and efficiently provides the rain parameter for any location within the studied map; (3) more speculatively, the 3D space-time interpolation approach can extrapolate to rain parameters at space-time resolutions shorter than those in the NIMROD databases.

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.

During the intensive observation period of the Watershed Allied Telemetry Experimental Research (WATER), a total of 1074 raindrop size distribution were measured by the Parsivel disdrometer, the latest state-of-the-art optical laser instrument. Because of the limited observation data in Qinghai-Tibet Plateau, the modelling behaviour was not well done. We used raindrop size distributions to improve the rain rate estimator of meteorological radar in order to obtain many accurate rain rate data in this area. We got the relationship between the terminal velocity of the raindrop and the diameter (mm) of a raindrop: v(D) = 4.67D0.53. Then four types of estimators for X-band polarimetric radar are examined. The simulation results show that the classical estimator R (ZH) is most sensitive to variations in DSD and the estimator R (KDP, ZH, ZDR) is the best estimator for estimating the rain rate. An X-band polarimetric radar (714XDP) is used for verifying these estimators. The lowest sensitivity of the rain rate estimator R (KDP, ZH, ZDR) to variations in DSD can be explained by the following facts. The difference in the forward-scattering amplitudes at horizontal and vertical polarizations, which contributes KDP, is proportional to the 3rd power of the drop diameter. On the other hand, the exponent of the backscatter cross-section, which contributes to ZH, is proportional to the 6th power of the drop diameter. Because the rain rate R is proportional to the 3.57th power of the drop diameter, KDP is less sensitive to DSD variations than ZH.

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.

[EN]The CRR (Convective Rainfall Rate) algorithm was developed to detect intense mesoscale convective cells and to screen the most probable precipitation associated. It estimates rainfall intensity using the three bands of the Meteosat-7 and matrices calibrated with earth-based radars. Calibration matrices were performed following an accurate version of the Rainsat techniques but combining the infrared bands to detect convective clouds. Matrices were developed, up for the North of Europe, over the Baltic countries, with data from the radar of the Baltex Project provided by the SMHI (Swedish Meteorological and Hydrological Institute) and for the South of Europe, over the Iberian Peninsula, with radar data as provided by the INM (Spanish Meteorological Institute). In the present research, the CRR calibration methodology is validated, an analysis of calibration matrices differences in both areas over Europe is detailed and CRR resulting images are verified in a qualitative manner using rainfall radar images as ground true. [ES]El algoritmo llamado CRR (Convective Rainfall Rate) ha sido desarrollado para detectar células convectivas mesoescalares y para monitorizar la precipitación asociada más probable. Es capaz de estimar intensidad de precipitación utilizando los tres canales del Meteosat-7 y matrices calibradas con datos de radares terrestres de precipitación. Estas matrices de precipitación han sido construidas a partir de las técnicas Rainsat pero combinando las dos bandas infrarrojas para favorecer la detección de nubosidad convectiva. Además, éstas han sido desarrolladas al norte del continente europeo sobre los países bálticos con datos de radar del proyecto Baltex proporcionados por el SMHI (Swedish Meteorological and Hydrological Institute) y al sur de Europa, sobre la Península Ibérica con datos de radar proporcionados por el INM (Instituto Nacional de Meteorología). En este trabajo se valida el método empleado de calibración de las matrices del CRR, se realiza un análisis de las matrices obtenidas al norte y sur de Europa, y finalmente una serie de imágenes CRR se verifican de forma cualitativa con respecto a las imágenes de radar.