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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.

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.

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.

Three global rainfall rate prediction methods are evaluated in their ability to estimate local precipitation statistics, which are the key to predict the impact of rain on the propagation of electromagnetic waves through the atmosphere. Specifically, the International Telecommunication Union-Radiocommunication Sector (ITU-R) P.837-6, model for rainfall statistics estimation (MORSE), and the ITU-R P.837-7 prediction methods are tested against long-term rainfall data collected in 19 sites in Ireland. The results indicate that the ITU-R P.837-7 prediction method delivers the best performance, and that both the ITU-R P.837-6 prediction method and MORSE exhibit a positive bias, likely due to the overestimation of the yearly rain amount in the maps used as input to such models. The results of the testing activity provide information on the accuracy of rainfall rate prediction methods at regional level, an important factor to consider given the direct link between the magnitude of rain-induced attenuation, and the operational frequency of wireless communication links.

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.

In radar observations of hydrometeors, the 0°C isotherm in the atmosphere (i.e., the freezing level) usually appears as a region of enhanced reflectivity. This region is known as the bright band (BB). In this study, observations over 12 months from a vertically pointing 35-GHz radar and a collocated disdrometer at the Natural Environment Research Council (NERC) Facility for Atmospheric and Radio Research (NFARR) are used to identify and compare microphysical differences between BB and non-brightband (NBB) periods. From these observations, the relationship between radar reflectivity Z and rainfall intensity R is found to be Z = 772R0.57 for BB periods and Z = 108R0.99 for NBB periods. Additionally, the brightband strength (BBS) was calculated using a novel method derived from the Michelson contrast equation in an attempt to explain the observed variability in BB precipitation. A series of Z–R relationships are computed with respect to BBS. The coefficients increase with increasing BBS from 227 to 926, while the exponents decrease with increasing BBS from 0.85 to 0.38. The results also indicate that NBB periods identified in the presence of a 0°C isotherm in other studies may be misclassified due to their inability to identify weak brightband periods. As such, it is hypothesized that NBB periods are solely due to warm rain processes.

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.

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.

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.

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.

Summary Ground clutter and beam blockage caused by complex terrain deteriorates the accuracy of radar quantitative precipitation estimations (QPE). To improve radar QPE, we have developed a technique for radar rainfall estimation, the Kyungpook National University Hybrid Surface Rainfall (KHSR), based on a two-dimensional hybrid surface consisting of the lowest radar bins that are immune to ground clutter, beam blockage, and non-meteorological echoes. The KHSR map is a composite of a ground echo mask, a beam blockage mask, and a rain echo mask, and it was applied to an operational S-band dual-polarimetric radar that scans six PPIs at a low elevation angle every 2.5 min. By using three rainfall estimators, R ( Z H ), R ( Z H , Z DR ), and R ( Z H , ξ DR ), this technique was compared with an operational Constant Altitude Plan Position Indicator (CAPPI) QPE of the Korea Meteorological Administration during a summer season from June–August 2012. In comparison with CAPPI, KHSR shows improved rainfall estimates for three algorithms, and it was more effective with dual-polarimetric rainfall algorithms than with single polarimetric rainfall algorithms. Error increased with increasing range from radar, but this increase was more rapid using CAPPI than using KHSR. KHSR using the R ( Z H , Z DR ) algorithm was the most accurate long range (>100 km from the radar) estimator.

The potential of rainfall-rate assignment using Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Instrument (SEVIRI) data is investigated. For this purpose, a new conceptual model for precipitation processes in connection with midlatitude cyclones is developed, based on the assumption that high rainfall rates are linked to a high optical thickness and a large effective particle radius, whereas low rainfall rates are linked to a low optical thickness and a small effective particle radius. Reflection values in the 0.56–0.71-μm (VIS0.6) and 1.5–1.78-μm (NIR1.6) channels, which provide information about the optical thickness and the effective radius, are considered in lieu of the optical and microphysical cloud properties. An analysis of the relationship between VIS0.6 and NIR1.6 reflection and the ground-based rainfall rate revealed a high correlation between the sensor signal and the rainfall rate. Based on these findings, a method for rainfall-rate assignment as a function of VIS0.6 and NIR1.6 reflection is proposed. The validation of the proposed technique showed encouraging results, especially for temporal resolutions of 6 and 12 h. This is a significant improvement compared to existing IR retrievals, which obtain comparable results for monthly resolution. The existing relationship between the VIS0.6 and NIR1.6 reflection values and the ground-based rainfall rate is corroborated with the new conceptual model. The good validation results indicate the high potential for rainfall retrieval in the midlatitudes with the high spatial and temporal resolution provided by MSG SEVIRI.

The presented paper describes an instrument called Aurometer which was designed for both atmospheric visibility and rainfall rate measurement. The principle of operation of Aurometer is based on determining the amount of light scattered by particles in the air that passes through the sample volume. The achieved results show that simultaneous estimation of the atmospheric visibility and rainfall rate is possible.

This paper describes and comments the results obtained applying a data processing method to a joint set of radar and a rain gauge data for estimating the 2-D rainfall field at ground averaged over a given observation time T and over a radar coverage area that includes a rain gauge network. The estimate of the rainfall field is based on the processing of a data set composed by rain gauge and horizontal reflectivity radar data gathered during a rainfall phenomenon. The procedure has been tested on an experimental data set collected in Tuscany in 1999.

— Various relationships between radar reflectivity Z and rainfall rate R commonly identified as Z-R relationships have been derived in order to provide better accuracy for rainfall rate estimation using weather radar. It is critical for the air traffic management at the airport to accurately detect existence of potential microburst and wind shear. There are numerous factors that can certainly affect the accuracy of Z-R relationships including poor hardware calibration. However, the inaccuracy of Z-R relationships also might be due to the differences between the precipitation at the ground level and the precipitation aloft because radar does not scan all the way down except at close range. Several Z-R relationships had also been proposed in the attempt to achieve better accuracy for rainfall estimates by radar system in the tropical region. Nonetheless, the most accurate Z-R relationship for Malaysia weather radar is yet to be investigated and to be identified within the study period. This paper presents the preliminary analyses of previously proposed Z-R relationships for Malaysia weather using new radar data and ground rainfall rate. Comparisons were made between values obtained from the previously proposed relationships for radar and the ground truth measurements. It was identified that the previously proposed relationships estimations are significantly lower than the rain gauge data.

Floods are one of the major disasters occurring all over the world, including Malaysia. It can lead to destruction of facilities, infrastructures as well as properties. Minimizing the risk of hazards and loss can be achieved by implementing several measures. Motivated from one of the biggest flood disasters ever occurred in the country, this monitoring system is developed as a means to reduce the risk of loss and damages. Monitoring rainfall rate may assist the community as it can provide early flood forecasting even though it cannot fully prevent the flood. Besides, it can give additional information on the probability of landslide occurrences. This paper presents the development of useful and reliable rainfall rate monitoring system for online hydrological stations in Kelantan. The whole processes in the development of this first prototype are conducted and performed using open-source software and tools such as Visual Basic and Quantum GIS (QGIS).

A comprehensive system that is used to invert the geophysical products from microwave measurements has recently been developed. This system, known as the Microwave Integrated Retrieval System (MiRS), ensures that the final solution is consistent with the measurements and, when used as input to the forward operator, fits them to within the instrument noise levels. In the presence of precipitation, this variational algorithm retrieves a set of hydrometeor products consisting of cloud liquid water, ice water, and rain water content profiles. This paper presents the development and assessment of the MiRS rainfall rate that is derived based on a predetermined relationship of the rainfall with these hydrometeor products. Since this relationship relies on the geophysical products retrieved by the MiRS as inputs and not on sensor-dependent parameters, the technique is suitable for all microwave sensors to which the MiRS is applied. This precipitation technique has been designed to facilitate its transition from research to operations when applied to current and future satellite-based sensors. Currently, the MiRS rainfall rate technique has been implemented operationally at the U.S. National Oceanic and Atmospheric Administration (NOAA) for the NOAA-18, NOAA-19, Metop-A Advanced Microwave Sounding Unit, and Microwave Humidity Sensor, as well as for the Defense Meteorological Satellite Program (DMSP)-F16 and DMSP-F18 Special Sensor Microwave Imager/Sounder microwave satellite sensors. For the validation of the MiRS rainfall rate technique, extensive comparisons with state-of-the-art precipitation products derived from rain gauge, ground-based radar, and satellite-based microwave observations are presented for different regions and seasons, and over land and ocean. The MiRS rainfall rate technique is shown to estimate precipitation, with a skill comparable to other satellite-based microwave precipitation algorithms, including the MSPPS, 3B40RT, and MWCOMB, while showing no discontinuities at coasts. This is a relevant result, considering that the MiRS is a system not merely designed to retrieve the rainfall rate but to consistently estimate a comprehensive set of atmospheric and surface parameters from microwave measurements.

Attenuation measured on terrestrial links can be used to estimate surface rainfall rates along a link path. There is current interest in the use of inverse methods to estimate rainfall over areas inferred from terrestrial links. A power-law relationship can be used to estimate rainfall rate from attenuation measured by a terrestrial link. However, the inverse method is simplified with a linear relationship between attenuation and rainfall rate when determining path averaged rainfall rates. This paper investigates power-law and linear relationships between rainfall rate and attenuation. It examines their goodness of fit for a range of frequencies and rainfall rates. Six years of disdrometer data from Chilbolton in the U.K. has been used to study both linear and power-law fits to attenuation and quantify the associated errors.

The paper describes the modelling of the average rainfall rate distribution measured at difierent locations in South Africa. There are three major aspects this paper addresses: to develop a rainfall rate model based on the maximum likelihood method (ML); to develop contour maps based on rainfall rate at 0:01% percentage of exceedence; and re-classiflcation of the ITU-R and Crane rain zones for the Southern Africa region. The work presented is based on flve- minute rainfall data converted to one-minute equivalent using a newly proposed hybrid method. The results are mapped and compared with conventional models such as the ITU-R model, Rice-Holmberg, Moupfouma and Crane models. The proposed rainfall rate models are compared and evaluated using root mean square and chi-square (´ 2 ) statistics. Then re-classiflcation of the rain zone using ITU-R and Crane designations is suggested for easy integration with existing radio planning tools. The rainfall rate contour maps at 0:01% percentage of exceedence are then developed for South Africa and its surrounding islands.

In 2012 the Météo France metropolitan operational radar network consists of 24 radars operating at C and S bands. In addition, a network of four X-band gap-filler radars is being deployed in the French Alps. The network combines polarimetric and nonpolarimetric radars. Consequently, the operational radar rainfall algorithm has been adapted to process both polarimetric and nonpolarimetric data. The polarimetric processing chain is available in two versions. In the first version, now operational, polarimetry is only used to correct for attenuation and filter out clear-air echoes. In the second version there is a more extensive use of polarimetry. In particular, the specific differential phase Kdp is used to estimate rainfall rate in intense rain. The performance of the three versions of radar rainfall algorithms (conventional, polarimetric V1, and polarimetric V2) at different frequency bands (S, C, and X) is evaluated by processing radar data of significant events offline and comparing hourly radar rainfall accumulations with hourly rain gauge data. The results clearly show a superior performance of the polarimetric products with respect to the nonpolarimetric ones at all frequency bands, but particularly at higher frequency. The second version of the polarimetric product, which makes a broader use of polarimetry, provides the best overall results.

It is well known that rainfall rate is enhanced over mountains due to orographic uplifting. It would be beneficial to rainfall nowcasting if the intensity of the orographic enhancement could be estimated using simple parameters. In the present study, we found a clear relationship between orographic enhancement of the rainfall rate and the movement speed of radar echoes in a case study of rainfall over mountains in the southwestern area of the Kanto District in Japan during Typhoon 0709, by using rainfall data derived from X-band polarimetric radar. The increasing rate of rainfall rate per unit altitude (ΔR/ΔH) showed a positive correlation (r = 0:95) with the movement speed of radar echoes (V) when V > 10 m s-1. Such a correlation suggests that V is an effective parameter for quickly estimating the orographic enhancement of rainfall, however, more case studies are required before it can be used in practical applications.

Tropical cyclones, also known as typhoons or hurricanes, are among the most devastating events in nature and often strike the western North Pacific region (including the Philippines, Taiwan, Japan, Korea, China, and others). This paper focuses on addressing the rainfall retrieval problem for quantitative precipitation forecast during tropical cyclones. In this study, Special Sensor Microwave Imager (SSM/I) data and Water Resources Agency (WRA) measurements of Taiwan were used to quantitatively estimate precipitation over the Tanshui River basin in northern Taiwan. Various retrievals for the rainfall rate over land are compared by five methods/techniques. They are the single-channel regression, multichannel linear regressions (MLR), scattering index over land approach (SIL), support vector regression (SVR), and the proposed SIL–SVR. This study collected 70 typhoons affecting the studied watershed over the past 12 years (1997–2008). The measurements of the SSM/I satellite comprise the brightness temperatures at 19.35, 22.23, 37.0, and 85.5 GHz. Overall, the results showed the approaches using the SVR and conjoined SVR and SIL performed better than regression and SIL methods according to their performances of the root-mean-square error (RMSE), bias ratio, and equitable threat score (ETS).

Rainfall-rate statistics are frequently derived on the basis of rain gauge recordings with effective integration times of 10 min or longer. The conversion of such data to equivalent statistics for an effective integration time of 1 min is very important to predict rainfall attenuation at a location accurately. Because of the limited availability of 1-min rainfall-rate data, conversion of available rainfall-rate distributions with longer integration times to the desired 1-min distributions is needed. Several methods for converting 60-min rainfall rates to 1-min rainfall rates are tested against measured rainfall rates from tropical, high-rainfall-rate regions. Segal’s method was found to perform the best overall when compared with other conversion methods.

The knowledge of 1-minute rainfall rate distribution is very important in order for the prediction of rainfall attenuation at any location. Due to the availability of 1-minute rainfall rate data is limited, conversion of rainfall rate distribution over a long integration time into the distribution for 1-minute is needed. Therefore several rainfall rate conversion methods were proposed.

Seasonal and spatial variation of the vertical gradient of rainfall rate was investigated using global precipitation data observed by the Precipitation Radar (PR) on the Tropical Rainfall Measuring Mission (TRMM) satellite. The vertical gradient was rendered by features of downward decreasing (DD) or downward increasing (DI) rainfall rate in the lower part of the profile. The DD profiles dominated tropical interior landmasses such as Africa and the Brazilian Plateau in summer. The DI profiles were observed over land in winter and over ocean except for regions with very little rainfall. In addition, DI profiles appeared during the height of the wet season even over the tropical landmasses, such as the mature monsoon period over inland India and over the Amazon River basin. Individual precipitation systems were also investigated in terms of their areally averaged DD and DI characteristics mainly over India. Deep (shallow) profiles tended to be DD (DI) for all seasons except the premonsoon season. A...

This paper deals with a new algorithm applicable to rainfall rate profiling with a rain-attenuating-frequency radar for vertical incidence from an air or space platform. The proposed algorithm is independent from external radar calibration which is especially difficult to perform in airborne or space-borne applications. In addition to backscattering data from raindrops, path-integrated rainfall rate is used to estimate a rainfall rate profile. The path-integrated rainfall rate may be estimated from surface echo attenuation or from brightness temperature measured with an auxiliary microwave radiometer. The performance of the proposed algorithm is evaluated by a computer simulation experiment assuming backscattering and attenuation models of the radar wave due to rain. Then, airborne radar data are analysed with the algorithm to demonstrate its validity.

Wireless communication systems operating at above 10 GHz are exposed to rain attenuation. Therefore, countries with high precipitation rate such as Malaysia, require careful planning before establishing a reliable wireless link. Signal attenuation due to rain can be measured or estimated, but it requires the knowledge of local 1-minute rainfall rate statistic. But for most part of the world, the rainfall data usually comes with higher integration time, such as 60-minute. As a result, the method to convert rainfall rate with higher integration time to 1-minute rainfall rate distribution is essential. In this study, hydrological data from five areas in East Malaysia is translated to 1-min and 60-min rainfall rate distribution. Then, five conversion models were used to convert 60-min rainfall rate to 1-min rainfall rate. From observation and conversion error analysis, this study found that Segal method performed the best when it is compared to other four conversion methods.

Malaysia is well known for its wet tropical climate and monsoon seasons which bring rainfall almost throughout the year. Therefore, designing wireless communication links above 10 GHz for Malaysian weather involves study of rainfall rate and its integration time. The knowledge of local 1-min rainfall rate statistic is the key input for the estimation of signal attenuation due to rain. Due to limitation of 1-min rain rate data availability, the conversion model is necessary to translate higher integration time rainfall rate to the required 1-min rainfall statistic. In this paper, rainfall data from six locations in the East Malaysia is acquired from a local hydrological agency and processed to a meaningful 1-min, 5-min and 10-min rainfall rate statistics. Then, four conversion models are used to convert from 5-min and 10-min rainfall rate to 1-min rainfall rate. From the conversion error analysis, it is found that the Emiliani et al conversion method performed the best for this study.

Precipitation plays a crucial role to the global water and energy cycle that governs the weather, climate, and ecological systems. Thorough understanding and accurate forecasting of precipitation is essential to the affairs of humans. The Tropical Rainfall Measuring Mission (TRMM), launched in 1997, is a joint space mission between NASA and the Japan Aerospace Exploration Agency (JAXA) designed to monitor and study tropical rainfall. The Precipitation Radar (PR) on board the TRMM satellite is the first space borne instrument, capable of providing high-resolution vertical profile of precipitation on a global scale. TRMM-PR operates at a single frequency of Ku- (13.6 GHz) band. The microphysical retrieval algorithms for TRMM-PR rely on the surface-reference technique (SRT) to estimate path attenuation and correct the measured Ku-band reflectivity. With the attenuation-corrected reflectivities, a modified Hitschfeld-Bordan method [1] is then used to retrieve limited drop size distribution (DSD) information, and the rainfall rate [2]. One disadvantage of single-frequency space borne radar such as TRMM-PR is that it is not easy to retrieve the DSD parameters completely. Therefore, k-Z and Z-R relationships, with their inherent assumptions, are used to estimate rainfall rate which is not sufficient to capture the variability of precipitation and has large uncertainty. Global Precipitation Measurement (GPM) mission is poised to be the next generation observations from space after the TRMM mission. GPM is a science mission with integrated applications goals for advancing the knowledge of the global water/energy cycle variability as well as improving weather, climate, and hydrological prediction capabilities through more accurate and frequent measurements of global precipitation. The GPM core satellite will be equipped with a dual-frequency precipitation radar (DPR) operating at Ku- (13.6 GHz) and Ka- (35.5 GHz) band [3]. Taking two independent sets of observation, DPR on aboard the GPM is expected to improve our knowledge of precipitation processes relative to the single-frequency (Ku- band) radar used in TRMM by providing greater dynamic range, more detailed information on microphysics. Two parameters of DSDs can be retrieved from dual-frequency observations and better accuracies in rainfall estimation can be achieved. Theoretically, rainfall rate is a function of rain drop size distribution and rain drop terminal velocity, R=0.67π∗10−3∫ v(D)D3N(D)dD. The most critical component in rainfall rate estimation is the time-space variation of drop size distribution. Le and Chandrasekar (2014) [4] developed a hybrid method to retrieve drop size distribution parameters for GPM-DPR. The hybrid method is a profile-based optimization algorithm with the philosophy to combine the attributes of forward method and linear constraints of DSDs in rain. Two of the gamma distribution parameters [5], Do and Nw, at surface are optimized when the deviation between estimates and observations are minimized. The hybrid method can be used to estimate DSDs at each space and temporal resolution of GPM-DPR observation. In this paper, rainfall rate is calculated using DSDs retrieved through the hybrid method [4] based on assumptions of particle terminal velocity. Data collected by GPM-DPR is capability to cover ±65° latitude of the earth with every 2–4 hours. Thus, a global rainfall map can be generated. In polarimetric radar system, rainfall rate can be estimated through dual-polarized radar parameter such as Zdr [6][7]. Zdr is called differential reflectivity and it is a function of particle characteristics itself. Similar of Zdr to the dual-polarization radar retrieval, there is a parameter called dual-frequency ratio (DFR) that plays an important role in the dual-frequency radar retrievals. DFR is defined as the difference of the radar reflectivity at two frequencies in decibels which carries information of single particle characteristics. In this study, we investigate potential relation between rainfall rate, reflectivity at Ku- band and DFR using theoretical simulation [8] and curve fitting. Figure 1 shows a scattergram of rainfall rate estimation from R(Zh, DFR) versus true rainfall rate. Both Zku and DFR are in linear form in this equation. This provides a direct estimation of rainfall rate without prior knowledge of drop size distribution. Since both reflectivity and dual frequency ratio are intrinsic values, attenuation correction is needed before rain rate can be estimated through R(Zh, DFR) equation. The hybrid method [4] described in previous paragraph could be one of the algorithms to perform attenuation correction. The global rainfall map generated through R(Zh, DFR) approach will be cross-compared with DSD approach described in the previous paragraph, as well as other approaches such as attenuation based rainfall rate. The comprehensive analysis of the three techniques are presented.