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The Global Precipitation Measurement mission is a major U.S.–Japan joint mission to understand the physics of the Earth’s global precipitation as a key component of its weather, climate, and hydrological systems. The core satellite carries a dual-precipitation radar and an advanced microwave imager which provide measurements to retrieve the drop size distribution (DSD) and rain rates using a Combined Radar-Radiometer Algorithm (CORRA). Our objective is to validate key assumptions and parameterizations in CORRA and enable improved estimation of precipitation products, especially in the middle-to-higher latitudes in both hemispheres. The DSD parameters and statistical relationships between DSD parameters and radar measurements are a central part of the rainfall retrieval algorithm, which is complicated by regimes where DSD measurements are abysmally sparse (over the open ocean). In view of this, we have assembled optical disdrometer datasets gathered by research vessels, ground stations, and aircrafts to simulate radar observables and validate the scattering lookup tables used in CORRA. The joint use of all DSD datasets spans a large range of drop concentrations and characteristic drop diameters. The scaling normalization of DSDs defines an intercept parameter NW, which normalizes the concentrations, and a scaling diameter Dm, which compresses or stretches the diameter coordinate axis. A major finding of this study is that a single relationship between NW and Dm, on average, unifies all datasets included, from stratocumulus to heavier rainfall regimes. A comparison with the NW–Dm relation used as a constraint in versions 6 and 7 of CORRA highlights the scope for improvement of rainfall retrievals for small drops (Dm < 1 mm) and large drops (Dm > 2 mm). The normalized specific attenuation–reflectivity relationships used in the combined algorithm are also found to match well the equivalent relationships derived using DSDs from the three datasets, suggesting that the currently assumed lookup tables are not a major source of uncertainty in the combined algorithm rainfall estimates.

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.

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.

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.

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 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.

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.

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.

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 goal of this paper is to calculate new calibration matrices using Rapid Scan (RSS) Meteosat Second Generation (MSG) measurements and to evaluate their impact on precipitation estimates for a territory of the Czech Republic. The calibration matrices are the most important part of the Convective Rainfall Rate algorithm, which uses the IR 10.8 μm, WV 6.2 μm and VIS 0.6 μm spectral SEVIRI (Spinning Enhanced Visible and Infrared Imager) channels of the MSG to assess satellite precipitation estimates (SPEs). The calibration matrices were calculated using Czech radar data from 21 summer days during which severe convection and heavy precipitation were observed. The resultant matrices were compared with those obtained using conventional 15 min MSG scans. The comparison showed significant differences in the calibration matrices, which resulted in differences in the estimated precipitation. The application of RSS data significantly increased the rain rates and improved the structure of the matrices; however, the matrices were subjectively modified to increase the accuracy of the resulting SPEs. The calibration matrices were also calibrated by shifting the radar data forward 5, 10, 15 and 20 min with respect to the MSG measurement, because some delay between the information obtained by the MSG and the radars was expected. The impact of the matrices was evaluated by verifying the SPEs with the radar-derived precipitation estimates merged with the rain gauge observations as the ground truth. The results showed that the calibration matrices that were based on the RSS data improved the categorical skill scores and reduced the mean error (ME), the mean absolute error (MAE), and root mean square error (RMSE) of SPEs. Subjectively, the estimated precipitation values are more realistic, the estimated maximum is closer to observations and convective cores are more pronounced and easily identifiable. The difference between the matrices calibrated by shifting the radar data in time was quite small, and the impact on the SPEs was not readily apparent. However, the time shifts of 15 and 20 min slightly improved the categorical skill scores and reduced the ME, MAE and RMSE.

— 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.

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.

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).

Satellite broadcasting in the 21-GHz band is expected to transmit large-capacity signals such as ultrahigh-definition TV. However, this band suffers from large amounts of rain attenuation. In this regard, we have been studying rain fading mitigation techniques, in which the radiation power is increased locally in the area of heavy rainfall. To design such a satellite broadcasting system, it is necessary to evaluate service availability when using the locally increased beam technique. The rain attenuation data should be derived from the rainfall rate data. We developed a method to transform rainfall rate into rain attenuation in the 21GHz band. Then, we performed a simulation that applied the method to the analysis of the service availability for an example phased array antenna configuration. The results confirmed the service availability increased with the locally increased beam technique.

This paper presents some preliminary observations of assessments regarding the precipitation intensity conversion methods from 60- to 1-min integration time. There are two conversion methods were identified and used for this findings; Rice-Holmberg and Khairolanuar et al. conversion methods. Different type of precipitation were analyzed and implemented in analytical method of Rice-Holmberg and characteristics of rainfall rate distributions were evaluated from the empirical method of Khairolanuar et al. Rainfall intensity data were acquired from Malaysia Meteorological Department (MMD). The rainfall rate data consist of twelve consecutive months from January to December 2009. The evaluations for the acquired data were carried out to produce annual rainfall rate cumulative distribution and as well as its cumulative distribution at 1-min integration time utilizing the aforementioned conversion methods. The comparisons of the performance of these two methods were also examined. Based on the evaluation, it can be observed that Rice-Holmberg and Khairolanuar et al. produced percentage errors around 19 % as compared to ITU-R P.837 at 0.01 % of time exceedance.

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...

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.

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.

The liquid/ice water paths (LWP/IWP) and the rainfall rate (RR) of precipitation systems over oceans are estimated using a combination of data from the special sensor microwave/imager (SSM/I) and the International Satellite Cloud Climatology Project (ISCCP). The retrieval scheme is based on microwave radiative transfer simulations. Collocated ISCCP cloud top temperatures are used to separate warm from cold precipitating clouds: cold precipitating clouds occur much more frequently than warm precipitating clouds and produce over 80% of the precipitation, but warm precipitating clouds are not negligible in the tropics and summer midlatitudes. SSM/I data are used to identify precipitating clouds: precipitating clouds are very rare (about 5% of all locations). Estimated IWP values, with mean about 7 mg/cm2, are quite variable, ranging from as little as 5 mg/cm2 to as much as 200 mg/cm2. The mean LWP in precipitating clouds is approximately 80 mg/cm2, occasionally reaching 1000 mg/cm2. Average RR (both cold and warm) is about 1.5 mm/hr, generally larger in the tropics than in midlatitudes. RR is larger in the northern hemispheric midlatitudes than in the southern midlatitudes. The global annual cycle of precipitation is dominated by tropical variations and is in phase with boreal seasons. The largest annual total precipitation occurs in the eastern Pacific (about 5000 mm). The subtropical precipitation minima may be underestimated because drizzle does not produce strong microwave signals.

In this paper, we propose a novel remote sensing method that is adequate for rainfall rate measurements in real time by means of tomographic processing applied to power attenuation measurements made across the microwave links defined by radio base station networks for mobile communication systems. A description of the tomographic algorithms we developed is presented together with some simulation results. These concern rainfall rate estimation applying such algorithms to the current radio base station arrangement over the city of Florence, Italy, while the rainfall field is simulated through weather radar data.

This paper present the rainfall rate obtained from the analysis of a meteorological radar data in Malaysia. Rainfall rate is an important parameter for a microwave link because it enables the attenuation due to rain to be determined. An important parameter in rain attenuation studies is the rain rate for 0.01% of the time or R/sub 0.01/. Design and system engineers use this value to construct communications system such that the link is available for 99.99% of the time. This result is obtained by utilizing the radar data from the Malaysian Meteorological Department. Knowing the rainfall rate, rain attenuation can be calculated. This information is useful for microwave link applications.