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Radio signal operating above 10 GHz tend to suffer signal losses, mostly due to hydrometeors such as rain. This phenomenon also called Rain fade. Radio engineers typically rely on sets of models and recommendations by ITU to predict rain fade and assign proper fade margin for radio network planning, but those models are extremely limited. Alternatively, engineers and radio planners can use meteorological data such as rain radar data to obtain spatial and temporal information on rainfall rate. One of the main issues is the temporal sampling or integration times of rainfall rate from rain radars. This paper studies the different established methods of converting different rainfall rate integration times into one-minute time, suitable for radio network planning and optimization. The methods wil be tested on NIMROD rain radars from UK.

Radio signal operating above 10 GHz tend to suffer signal losses, mostly due to hydrometeors such as rain. This phenomenon also called Rain fade. Radio engineers typically rely on sets of models and recommendations by ITU to predict rain fade and assign proper fade margin for radio network planning, but those models are extremely limited. Alternatively, engineers and radio planners can use meteorological data such as rain radar data to obtain spatial and temporal information on rainfall rate. One of the main issues is the temporal sampling or integration times of rainfall rate from rain radars. This paper studies the different established methods of converting different rainfall rate integration times into one-minute time, suitable for radio network planning and optimization. The methods wil be tested on NIMROD rain radars from UK.

Reliable rainfall rate complementary cumulative distributions are critical for the design of microwave communications systems operating above around 8 GHz. This Letter presents the results of the analysis of more than 5 years of 1-minute integrated rainfall accumulation data for 12 stations. This new dataset will prove useful considering the sharing analyses that must be executed for IMT services in the 24.25–27.5, 37–43.5, 45.5–47, 47.2–48.2 and 66–71 GHz spectrum bands. The resulting statistics can complement the entries in the database of ITU-R Study Group 3 for the region.

Reliable rainfall rate complementary cumulative distributions are critical for the design of microwave communications systems operating above around 8 GHz. This Letter presents the results of the analysis of more than 5 years of 1-minute integrated rainfall accumulation data for 12 stations. This new dataset will prove useful considering the sharing analyses that must be executed for IMT services in the 24.25–27.5, 37–43.5, 45.5–47, 47.2–48.2 and 66–71 GHz spectrum bands. The resulting statistics can complement the entries in the database of ITU-R Study Group 3 for the region.

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

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

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

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

The rapid development of the radio communications system, especially in developed countries, has drawn the attention of telecommunication systems engineers to explore the frequency band above the Ku band. Because radio communication systems operating in the frequency band above the Ku band (10 G Hz) suffer from rain attenuation during rainy conditions, prediction of rain attenuation using a 1-min rainfall rate distribution is indeed vital. However, a 1-min rainfall rate distribution is not widely available compared to rainfall rate distributions with longer integration times. Therefore, a suitable conversion method is required to predict 1-min rainfall rate distributions of distinct integration times. This paper presents several conversion methods such as Segal, Burgueno et al., Chebil and Rahman, Joo et al., EXCELL RSC and LG . The Segal method provides an overall Root Mean Square (RMS ) error below 5% at different integration times and is suitable to be used in Malaysia., Brzi razvoj sustava radio komunikacija, a što je naročito izraženo u razvijenim zemljama, potaknuo je inženjere na istraživanje frekvencijskog pojasa iznad tzv. Ku pojasa. Naime, radiokomunikacijski sustavi koji rade u frekvencijskom pojasu iznad Ku-pojasa (10 GHz) podložni su prigušenju u oborinskim uvjetima. Stoga je predviđanje atenuacije radio signala korištenjem 1-min intenziteta oborine od velike važnosti. Međutim, za razliku od razdioba intenziteta oborine za duža kumulacijska vremena, razdiobe 1-min intenziteta nisu široko dostupne. Stoga je neophodna metoda konverzije za predviđanje distribucije 1-min intenziteta oborine za različita kumulacijska vremena. U ovom radu je prikazano nekoliko metoda konverzije kao što su metode Segala, Burguena i suradnika, Chebila i Rahmana, Jooa i suradnika, te EXCELL RSC i LG metoda. Metoda Segala daje ukupnu srednju kvadratnu pogrešku (Root Mean Square Error – RMS ) ispod 5% za različita kumulacijska vremena i pokazuje se prikladnom za upotrebu u Maleziji.

The rapid development of the radio communications system, especially in developed countries, has drawn the attention of telecommunication systems engineers to explore the frequency band above the Ku band. Because radio communication systems operating in the frequency band above the Ku band (10 G Hz) suffer from rain attenuation during rainy conditions, prediction of rain attenuation using a 1-min rainfall rate distribution is indeed vital. However, a 1-min rainfall rate distribution is not widely available compared to rainfall rate distributions with longer integration times. Therefore, a suitable conversion method is required to predict 1-min rainfall rate distributions of distinct integration times. This paper presents several conversion methods such as Segal, Burgueno et al., Chebil and Rahman, Joo et al., EXCELL RSC and LG . The Segal method provides an overall Root Mean Square (RMS ) error below 5% at different integration times and is suitable to be used in Malaysia., Brzi razvoj sustava radio komunikacija, a što je naročito izraženo u razvijenim zemljama, potaknuo je inženjere na istraživanje frekvencijskog pojasa iznad tzv. Ku pojasa. Naime, radiokomunikacijski sustavi koji rade u frekvencijskom pojasu iznad Ku-pojasa (10 GHz) podložni su prigušenju u oborinskim uvjetima. Stoga je predviđanje atenuacije radio signala korištenjem 1-min intenziteta oborine od velike važnosti. Međutim, za razliku od razdioba intenziteta oborine za duža kumulacijska vremena, razdiobe 1-min intenziteta nisu široko dostupne. Stoga je neophodna metoda konverzije za predviđanje distribucije 1-min intenziteta oborine za različita kumulacijska vremena. U ovom radu je prikazano nekoliko metoda konverzije kao što su metode Segala, Burguena i suradnika, Chebila i Rahmana, Jooa i suradnika, te EXCELL RSC i LG metoda. Metoda Segala daje ukupnu srednju kvadratnu pogrešku (Root Mean Square Error – RMS ) ispod 5% za različita kumulacijska vremena i pokazuje se prikladnom za upotrebu u Maleziji.

Lau, Stephen Po Wing., "August 2011.", Thesis (M.Phil.)--Chinese University of Hong Kong, 2011., Includes bibliographical references (leaves 62-66)., s in English and Chinese., List of figures --- p.vi, List of tables --- p.ix, Chapter Chapter 1: --- Background --- p.1, Chapter Chapter 2: --- Changes in Rainfall Characteristics in Hong Kong --- p.3, Chapter 2.1 --- Introduction --- p.3, Chapter 2.2 --- Data --- p.5, Chapter 2.3 --- Method --- p.6, Chapter 2.3.1 --- Linear Regression Analysis --- p.8, Chapter 2.3.2 --- Empirical Mode Decomposition --- p.9, Chapter 2.4 --- Result --- p.12, Chapter 2.4.1 --- Rainfall Rate Categories --- p.12, Chapter 2.4.2 --- Rainfall Events Statistics --- p.20, Chapter 2.4.3 --- Diurnal Variation --- p.26, Chapter 2.4.4 --- Rainfall Rate Distribution --- p.30, Chapter Chapter 3: --- Reflectivity-rainfall Rate Relationships in Hong Kong --- p.33, Chapter 3.1 --- Introduction --- p.33, Chapter 3.2 --- Data --- p.35, Chapter 3.3 --- Method --- p.37, Chapter 3.3.1 --- Linear Regression Analysis --- p.37, Chapter 3.4 --- Result --- p.38, Chapter 3.4.1 --- Comparison of Rainfall Rate from Various Sources --- p.39, Chapter 3.4.2 --- Raindrop Size Distributions under Various Classification Schemes --- p.42, Chapter 3.4.3 --- Z-R Relationships Derived from Various Sources --- p.48, Chapter Chapter 4: --- Conclusion --- p.58, Bibliography --- p.62, http://library.cuhk.edu.hk/record=b5894868, Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Lau, Stephen Po Wing., "August 2011.", Thesis (M.Phil.)--Chinese University of Hong Kong, 2011., Includes bibliographical references (leaves 62-66)., s in English and Chinese., List of figures --- p.vi, List of tables --- p.ix, Chapter Chapter 1: --- Background --- p.1, Chapter Chapter 2: --- Changes in Rainfall Characteristics in Hong Kong --- p.3, Chapter 2.1 --- Introduction --- p.3, Chapter 2.2 --- Data --- p.5, Chapter 2.3 --- Method --- p.6, Chapter 2.3.1 --- Linear Regression Analysis --- p.8, Chapter 2.3.2 --- Empirical Mode Decomposition --- p.9, Chapter 2.4 --- Result --- p.12, Chapter 2.4.1 --- Rainfall Rate Categories --- p.12, Chapter 2.4.2 --- Rainfall Events Statistics --- p.20, Chapter 2.4.3 --- Diurnal Variation --- p.26, Chapter 2.4.4 --- Rainfall Rate Distribution --- p.30, Chapter Chapter 3: --- Reflectivity-rainfall Rate Relationships in Hong Kong --- p.33, Chapter 3.1 --- Introduction --- p.33, Chapter 3.2 --- Data --- p.35, Chapter 3.3 --- Method --- p.37, Chapter 3.3.1 --- Linear Regression Analysis --- p.37, Chapter 3.4 --- Result --- p.38, Chapter 3.4.1 --- Comparison of Rainfall Rate from Various Sources --- p.39, Chapter 3.4.2 --- Raindrop Size Distributions under Various Classification Schemes --- p.42, Chapter 3.4.3 --- Z-R Relationships Derived from Various Sources --- p.48, Chapter Chapter 4: --- Conclusion --- p.58, Bibliography --- p.62, http://library.cuhk.edu.hk/record=b5894868, Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

The prediction of the power backscattered by the sea surface in the presence of rainfall is the object of this paper. An electromagnetic (e.m.) model predicting Normalized Radar Cross Section (NRCS) of such surface, must conveniently account for both a large scale roughness roughness due to wind and a small scale roughness due to raindrop splashes. While several models are available in the literature for wind-induced roughness, only few experimental results or theoretical studies concerning additional rainfall-induced roughness are available. Here we describe an e.m. model that accounts for the effects of the raindrop splashes, and discuss some related results. An improved algorithm is then proposed here for retrieving rainfall rate profiles by means of spaceborne rain radars, which utilizes the relationship between sea NRCS and rainfall rate.

The prediction of the power backscattered by the sea surface in the presence of rainfall is the object of this paper. An electromagnetic (e.m.) model predicting Normalized Radar Cross Section (NRCS) of such surface, must conveniently account for both a large scale roughness roughness due to wind and a small scale roughness due to raindrop splashes. While several models are available in the literature for wind-induced roughness, only few experimental results or theoretical studies concerning additional rainfall-induced roughness are available. Here we describe an e.m. model that accounts for the effects of the raindrop splashes, and discuss some related results. An improved algorithm is then proposed here for retrieving rainfall rate profiles by means of spaceborne rain radars, which utilizes the relationship between sea NRCS and rainfall rate.

The problem of improving estimates of rainfall intensity over the sea surface through spaceborne rain radars is addressed. The backscattered signal is composed of volumetric contribution due to rainfall and of the sea surface contribution. When trying to estimate the NRCS of the sea surface, one of the major difficulties is that different scale of roughness of the sea surface should be accounted for in the same e.m. model: the larger due to wind and the smaller due to the raindrop splashes. While in the first case several models are available in the literature, in the second case only a few experimental results or theoretical studies are at disposal. In this paper, a model which accounts for the additional roughness due to the effects of the raindrop splashes is analysed. Furthermore, an enhanced algorithm is proposed here for retrieving rainfall rate profiles, which utilises the relationship between sea NRCS and rainfall rate.

The problem of improving estimates of rainfall intensity over the sea surface through spaceborne rain radars is addressed. The backscattered signal is composed of volumetric contribution due to rainfall and of the sea surface contribution. When trying to estimate the NRCS of the sea surface, one of the major difficulties is that different scale of roughness of the sea surface should be accounted for in the same e.m. model: the larger due to wind and the smaller due to the raindrop splashes. While in the first case several models are available in the literature, in the second case only a few experimental results or theoretical studies are at disposal. In this paper, a model which accounts for the additional roughness due to the effects of the raindrop splashes is analysed. Furthermore, an enhanced algorithm is proposed here for retrieving rainfall rate profiles, which utilises the relationship between sea NRCS and rainfall rate.

An experiment was preformed in the Gulf Mexico to characterize the underwater sound generated by the heavy precipitation and to determine if rainfall rate can be measured using underwater sound. During this stage of the experiment, twenty-two data sets were recorded with rainfall rates up to 340 mm/ hr. For a given rainfall rate, it is found that sound levels from heavy convective precipitation are higher at the beginning of the storm and when rainfall rate is increasing than at the end of the storm event or when rainfall rates are decreasing. This may be due to changes in the drop size distribution during the life cycle of the storm or to variations in the temperature difference between the raindrop and the ocean surfaces. Very heavy rainfall generates near surface bubble layers or bubble clouds which attenuate sound energy at higher frequencies. The distinctive 15 kHz peak in the sound spectrum for light rain or absent during heavy rain suggesting that the sound production mechanism previously identified for small drops is suppressed by heavy rain even though those small drops are undoubtedly present during heavy rainfall rates. These data show a very high correlation between underwater sound level and the logarithm of the rainfall rate except when high wind speeds and high rainfall rates are present. An empirical rainfall rate algorithm for convective precipitation is proposed suggesting that sound energy is directly proportional to rainfall rate.

An experiment by the Naval Postgraduate School and the National Data Buoy Center was performed in the Gulf of Mexico to characterize the underwater sound generated by heavy precipitation and to determine if rainfall rates of heavy precipitation can be measured using underwater sound. During this stage of the experiment, twentytwo data sets were recorded with rainfall rates up to 340 mm/hr. For a given rainfall rate, it is found that sound levels from heavy convective precipitation are higher at the beginning of the storm and when the rainfall rate is increasing than at the end of the storm event or when rainfall rates are decreasing. This may be due to changes in the drop size distribution during the life cycle of the storm or to variations in the temperature difference between the raindrop and the ocean surface. Very heavy rainfall (rate > 150 mm/hr) generates near surface bubble layers or bubble clouds which attenuate sound energy at higher frequencies (>15 kHz). The distinctive 15 kHz peak in the sound spectrum for light rain is absent during heavy rain suggesting that the sound production mechanism previously identified for small drops (0.8 - 1.1 mm in diameter) is suppressed by heavy rain even though those small drops are undoubtedly present during heavy rainfall rates. These data show a very high correlation between underwater sound level and the logarithm of the rainfall rate except when high wind speeds (> 10 m/s) and high rainfall rates (> 150 mm/hr) are present. An empirical rainfall rate algorithm for con-vcctive precipitation is proposed suggesting that sound energy is directly proportional to rainfall rate, however any empirical algorithm which does not adjust for changing. storm characteristics should be used with caution.

Vertical rainfall profile retrieval based on reflectivity data collected by spaceborne rain radars can be improved through the techniques that exploit an estimation of the sea surface Normalised Radar Cross Section (NRCS) as an additional information. However, errors that can currently be made in predicting the sea surface NRCS may significantly affect their performance. Therefore, in this paper we first address the problem to evaluate the NCRS of the sea surface perturbed by rain, when observed at nadir. For this purpose, the dominant effect of ring waves generated by rainfall is considered. The joint effect of wind is also considered. The proposed model is based on the Full Wave Model (FWM) theory. Some comparisons are made with an alternative, less flexible model based on the Integral Equation Model (IEM) theory, and partial comparisons are also made with experimental data, which authorize to consider the proposed model well grounded and exploitable for application. Then, we show that the model can be usefully exploited to improve rainfall rate vertical profile retrieval over the sea surface, in the case of nadir looking, single frequency radars.

Vertical rainfall profile retrieval based on reflectivity data collected by spaceborne rain radars can be improved through the techniques that exploit an estimation of the sea surface Normalised Radar Cross Section (NRCS) as an additional information. However, errors that can currently be made in predicting the sea surface NRCS may significantly affect their performance. Therefore, in this paper we first address the problem to evaluate the NCRS of the sea surface perturbed by rain, when observed at nadir. For this purpose, the dominant effect of ring waves generated by rainfall is considered. The joint effect of wind is also considered. The proposed model is based on the Full Wave Model (FWM) theory. Some comparisons are made with an alternative, less flexible model based on the Integral Equation Model (IEM) theory, and partial comparisons are also made with experimental data, which authorize to consider the proposed model well grounded and exploitable for application. then, we show that the model can be usefully exploited to improve rainfall rate vertical profile retrieval over the sea surface, inthe case of nadir looking, single frequency radars.

Vertical rainfall profile retrieval based on reflectivity data collected by spaceborne rain radars can be improved through the techniques that exploit an estimation of the sea surface Normalised Radar Cross Section (NRCS) as an additional information. However, errors that can currently be made in predicting the sea surface NRCS may significantly affect their performance. Therefore, in this paper we first address the problem to evaluate the NCRS of the sea surface perturbed by rain, when observed at nadir. For this purpose, the dominant effect of ring waves generated by rainfall is considered. The joint effect of wind is also considered. The proposed model is based on the Full Wave Model (FWM) theory. Some comparisons are made with an alternative, less flexible model based on the Integral Equation Model (IEM) theory, and partial comparisons are also made with experimental data, which authorize to consider the proposed model well grounded and exploitable for application. then, we show that the model can be usefully exploited to improve rainfall rate vertical profile retrieval over the sea surface, inthe case of nadir looking, single frequency radars.

Vertical rainfall profile retrieval based on reflectivity data collected by spaceborne rain radars can be improved through the techniques that exploit an estimation of the sea surface Normalised Radar Cross Section (NRCS) as an additional information. However, errors that can currently be made in predicting the sea surface NRCS may significantly affect their performance. Therefore, in this paper we first address the problem to evaluate the NCRS of the sea surface perturbed by rain, when observed at nadir. For this purpose, the dominant effect of ring waves generated by rainfall is considered. The joint effect of wind is also considered. The proposed model is based on the Full Wave Model (FWM) theory. Some comparisons are made with an alternative, less flexible model based on the Integral Equation Model (IEM) theory, and partial comparisons are also made with experimental data, which authorize to consider the proposed model well grounded and exploitable for application. Then, we show that the model can be usefully exploited to improve rainfall rate vertical profile retrieval over the sea surface, in the case of nadir looking, single frequency radars.

Summary: Accuracy in estimation of precipitation can be achieved by utilizing the combination of spatial radar reflectivity data (Z) and the high resolution temporal rain gage based rainfall data (R). The study proposes the use of optimization models for optimizing the Z-R coefficients and exponents for different storm types and seasons. Precipitation data based on reflectivity, collected from National Climatic Data Center (NCDC) and rain gage data from Southwest Florida Water Management District (SWFWMD) over same temporal resolutions were analyzed using the Rain-Radar- Retrieval (R3) system developed as a part of the study. Optimization formulations are proposed to obtain optimal coefficients and exponents in the Z-R relationships for different seasons and objective selection of storm-type specific Z-R relationships. Different approaches in selection of rain gage stations and selection of events for optimization are proposed using gradient based solver and genetic algorithms., Kandarp Pattani., Thesis (M.S.C.S.)--Florida Atlantic University, 2010., Includes bibliography., Electronic reproduction. Boca Raton, Fla., 2010. Mode of access: World Wide Web.

Weather radar systems are very suitable tools for the monitoring of extreme rainfall events providing measurements with high spatial and temporal resolution over a wide geographical area. Nevertheless, radar rainfall retrieval at C-band is prone to several error sources, such as rain path attenuation which affects the accuracy of inversion algorithms. In this paper, the so-called rain profiling techniques (namely the surface reference method FV and the polarimetric method ZPHI) are applied to correct rain path attenuation and a new neural network algorithm is proposed to estimate the rain rate from the corrected measurements of reflectivity and differential reflectivity. A stochastic model, based on disdrometer measurements, is used to generate realistic range profiles of raindrop size distribution parameters while a T-matrix solution technique is adopted to compute the corresponding polarimetric variables. A sensitivity analysis is performed in order to evaluate the expected errors of these methods. It has been found that the ZPHI method is more reliable than FV, being less sensitive to calibration errors. Moreover, the proposed neural network algorithm has shown more accurate rain rate estimates than the corresponding parametric algorithm, especially in presence of calibration errors

Rare usage of Free Space Optical (FSO) communications in Malaysia might be related to environmental factors. Unguided beam is also known as free space optics technology or ‘optical wireless’ or ‘infrared broadband’. This project explores the propagation of point-to-point FSO due to weather conditions. Weather severity has detrimental impact on FSO transmission performance. The impact could result in insufficient quality of transmission and communication failure. Therefore FSO implementation requires thorough study of local weather patterns. By studying the local weather pattern, scattering coefficient and atmospheric attenuation could be derived to determine weather severity in this area. This information could help in predicting possible impact on data transmission quality and transmission interference system operation. In addition, FSO system design could be improved and altered to overcome possible interference and optimize system operation.This study is focused on the effect of rain and haze in Subang Airport. The Climate Division of Meteorological Department, Petaling Jaya branch, provided the data on rain and haze, which were collected hourly throughout year 2000. The rain data, which were collected in mm/hr, are categorized into three groups: heavy rainfall, moderate rainfall and light rainfall. The haze data was collected based on visibility distance in km. The visibility on hazy days is categorized into low visibility and average visibility. The non-selective scattering contributed dominant loss on rainy days and Mie scattering on hazy days. The non-selective scattering is wavelength independent and Mie scattering is wavelength dependent. The wavelength of 1550nm is selected because it is not harmful to the human eyes, not aggressive to the environment and contributes to better performances. The scattering coefficient and atmospheric attenuation for rain and hazy days are determined by using Stroke Law and Beer’s Law. The atmospheric attenuation due to scat

Rare usage of Free Space Optical (FSO) communications in Malaysia might be related to environmental factors. Unguided beam is also known as free space optics technology or ‘optical wireless’ or ‘infrared broadband’. This project explores the propagation of point-to-point FSO due to weather conditions. Weather severity has detrimental impact on FSO transmission performance. The impact could result in insufficient quality of transmission and communication failure. Therefore FSO implementation requires thorough study of local weather patterns. By studying the local weather pattern, scattering coefficient and atmospheric attenuation could be derived to determine weather severity in this area. This information could help in predicting possible impact on data transmission quality and transmission interference system operation. In addition, FSO system design could be improved and altered to overcome possible interference and optimize system operation.This study is focused on the effect of rain and haze in Subang Airport. The Climate Division of Meteorological Department, Petaling Jaya branch, provided the data on rain and haze, which were collected hourly throughout year 2000. The rain data, which were collected in mm/hr, are categorized into three groups: heavy rainfall, moderate rainfall and light rainfall. The haze data was collected based on visibility distance in km. The visibility on hazy days is categorized into low visibility and average visibility. The non-selective scattering contributed dominant loss on rainy days and Mie scattering on hazy days. The non-selective scattering is wavelength independent and Mie scattering is wavelength dependent. The wavelength of 1550nm is selected because it is not harmful to the human eyes, not aggressive to the environment and contributes to better performances. The scattering coefficient and atmospheric attenuation for rain and hazy days are determined by using Stroke Law and Beer’s Law. The atmospheric attenuation due to scat

In this paper, a variational data assimilation approach is used to assimilate the rain rate (RR) data together with precipitable water (PW) measurements from Experiment on Rapidly Intensifying Cyclones over the Atlantic (ERICA) (4-5 January 1989; IOP-4 cyclone). The PW and RR, which are assimilated into the MM5 model, are computed from the Special Sensor Microwave/Imager (SSM/I) raw data-brightness temperatures, via a statistical regression method. The SSM/I-derived RR and PW at 0000 UTC and/or 0930 UTC are assimilated into the MM5. The data at 2200 UTC are used for verification of the prediction results. Numerical experiments are performed using the Penn State/NCAR mesoscale model version 5 (MM5). Two horizontal resolutions of 50 km and 25 km are used in our studies. Comparisons are made between the experiments with and without SSM/I-measured PW and RR observations. Results from these experiments showed that: (1) The MM5 simulated a well-behaved but slightly less intense, position-shifted cyclogenesis episode based on the NCEP analysis enhanced with only radiosonde and surface observations through a Cressman-type of objective analysis. (2) The satellite-derived PW and RR observations were assimilated successfully into the MM5 model by a variational method. The cost function which measures the distance between the model predicted and the observed PW and RR decreased by about one order of magnitude. (3) Assimilation of PW and RR significantly improved the cyclone prediction, reflected mostly in the cyclone's track, the associated frontal structure and the associated precipitation along the front. The model's spin-up problem during the simulation was greatly reduced after assimilating the PW and RR information into the model initial conditions. (4) Sensitivity experiments of RR assimilation indicated that the impact on the results of RR assimilation was less sensitive to errors in the magnitude estimate than errors in the RR location.

The surface-referenced algorithm, referred as kZS, performs at its best when uncertainty related to sea surface normalized radar cross section (NRCS) is limited. The kZS algorithm is upgraded based on the prediction of the NRCS of the water surface roughened by both wind and rainfall. Such prediction relies on the full wave model (FWM). Improved performance of the rainfall profile retrieval scheme is demonstrated via simulations carried out at 13.75 GHz for different rainfall rates over the sea surface and different rainfall profiles. All of them showed that the rainfall profile retrieval accuracy can greatly benefit from a more accurate prediction of NRCS.

The surface-referenced algorithm, referred as kZS, performs at its best when uncertainty related to sea surface normalized radar cross section (NRCS) is limited. The kZS algorithm is upgraded based on the prediction of the NRCS of the water surface roughened by both wind and rainfall. Such prediction relies on the full wave model (FWM). Improved performance of the rainfall profile retrieval scheme is demonstrated via simulations carried out at 13.75 GHz for different rainfall rates over the sea surface and different rainfall profiles. All of them showed that the rainfall profile retrieval accuracy can greatly benefit from a more accurate prediction of NRCS.

An experiment by the Naval Postgraduate School and the National Data Buoy Center was performed in the Gulf of Mexico to characterize the underwater sound generated by heavy precipitation and to determine if rainfall rates of heavy precipitation can be measured using underwater sound. During this stage of the experiment, twentytwo data sets were recorded with rainfall rates up to 340 mm/hr. For a given rainfall rate, it is found that sound levels from heavy convective precipitation are higher at the beginning of the storm and when the rainfall rate is increasing than at the end of the storm event or when rainfall rates are decreasing. This may be due to changes in the drop size distribution during the life cycle of the storm or to variations in the temperature difference between the raindrop and the ocean surface. Very heavy rainfall (rate > 150 mm/hr) generates near surface bubble layers or bubble clouds which attenuate sound energy at higher frequencies (>15 kHz). The distinctive 15 kHz peak in the sound spectrum for light rain is absent during heavy rain suggesting that the sound production mechanism previously identified for small drops (0.8 - 1.1 mm in diameter) is suppressed by heavy rain even though those small drops are undoubtedly present during heavy rainfall rates. These data show a very high correlation between underwater sound level and the logarithm of the rainfall rate except when high wind speeds (> 10 m/s) and high rainfall rates (> 150 mm/hr) are present. An empirical rainfall rate algorithm for con-vcctive precipitation is proposed suggesting that sound energy is directly proportional to rainfall rate, however any empirical algorithm which does not adjust for changing. storm characteristics should be used with caution., http://archive.org/details/ambientsoundinoc1094526348, Lieutenant, United States Navy, Approved for public release; distribution is unlimited.

This report provides a new model of hydrometeors and associated cloud-water content from the surface to 20 km. The model profiles at altitude were developed based on five surface rainfall rates: 36, 84, 168, 432, and 1872 mm/hr. The first three rates correspond to a frequency of occurrence of 0.5 percent, 0.1 percent, and 0.01 percent of the time during the worst month in the most severe area of the world for intense rainfall. The last two are the 42- and 1-min world record rainfalls. The surface rainfall rates were extrapolated aloft using results from previous studies. A large sample of drop-size distributions from intense rainfall collected during reconnaisance of Atlantic hurricanes/ tropical storms was analyzed. The data set was normalized and fit by a gamma distribution. This was used to specify the drop-size distributions and liquid water content for rainfall rates specifies at the surface and aloft. Concurrent cloud-water content was estimated. Results are presented at 2-km intervals.

This report summarizes the work accomplished during the first phase of an investigation concerning methods of introducing digitized satellite imagery into short-range, objective forecasting operations. The data archive being assembled for this study is described, with particular attention given to the steps taken to maximize the accuracy of the satellite imagery. These steps included 'fine tuning' the navigation and selecting procedures for 'normalizing' the data by correcting for the effects of Lambertian and anisotropic scattering. Consistency of the data, spatial and temporal, was tested by analysis of ground reflectance during cloudless days, and a pilot test of the specification of single layers of clouds was conducted. Both of these tests gave encouraging results. An investigation of specifying precipitation rate, using just the visible reflectance and infrared temperature of the cloud top, also produced good results. Nomograms for the average rate during the hour following the satellite observation, as well as for the probability of observing more than 0.01 in. and 0.10 in. of precipitation, are illustrated. Two appendices present the geometrical and optical equations relevant to the investigation. (Author)

The purpose of this study is to determine water vapor and liquid water content from the Nimbus 6 SCAMS instrument over land surfaces. The radiative properties of clouds and precipitation in the SCAMS channels are investigated using the discrete-ordinate method for approximating the solution of the radiative transfer as it is applied to nonisothermal, inhomogeneous cloudy atmospheres. An examination of the problem of variations in surface emissivity over land in the microwave spectrum is included. Analysis of the upwelling radiances from the model in the presence of clouds indicates that the concentration of water vapor and liquid water in atmospheres over land surfaces has a consistent and predictable effect on the observed brightness temperatures. The reuslts of the theoretical calculations are parameterized and an empirical method to derive water vapor and liquid water from the observed upwelling radiances is described. Satellite passes from five days over the United States are used to test the empirical parameterizations of the theoretical results. The empirically derived liquid water contents for two days are compared with synoptic discussions and NOAA 4 satellite mosaics, as well as previous infrared research for the same time period (Feddes and Liou, 1978).

An important characteristic of rainfall levels at a particular place is the statistical distribution of rainfall rate. In this paper, 1-minute, 5-minute and 30-minute integration time rainfall data were obtained from various weather stations in the Physics Department of Federal University of Technology, Minna, North Central Nigeria. The essence is to derive conversion factors that can be used to predict 1-minute integration time rainfall rate from rainfall rates of other integration times. The results obtained revealed that a power law relationship exist between 1-minute (R1) and the equiprobable 5-minute rain rate (R5), derived as R1 = 1.414 R51.640; and between 1-minute (R1) and the equiprobable 30-minute rain rate (R30), derived as R1 = 0.960 R301.897. Also, conversion factors Ce and CR for 1-minute rain rate statistics were derived. The conversion factors Ce derived for T = 5-minute and ? = 1-minute are 1.08, 1.05, 0.98 and 1.04 respectively for 40 mm/h, 60 mm/h, 80 mm/h and 100 mm/h rain rates, while the conversion factors CR derived for ? = 1-minute as against T = 5-minute are 0.70 and 0.71 for R0.01 = 70 mm/h and R0.001 = 100 mm/h respectively. In addition, the CR derived for ? = 1-minute as against T = 30-minute are 0.06 and 0.25 for R0.01 = 6 mm/h and R0.001 = 35 mm/h respectively.

Z/R relationship is a power law relationship between radar reflectivity (Z) and rainfall rate (R). The relationship is expressed as Z = aRb where a and b are correlated with drop size distribution (DSD) and vary across locations. Using a Z/R relationship to translate radar reflectivity to rainfall rate can allow for real-time precipitation monitoring with a high temporal and spatial resolution. A dataset of 12 cases in Georgia from December 2021 to November 2022 was examined using the Georgia Weather Network rain gauge system and the KFFC radar to optimize the best Z/R relationship for each case. Radar-based precipitation estimates employed with a Dual Stratiform/Convective Z/R relationship outperformed the Single, Marshall-Palmer, and Summer Deep Convection relationships in all 12 cases. Both the weighted and unweighted Dual Z/R relationships obtained the lowest RMSE. The weighted Dual Z/R relationships had fewer stations over- or underestimating by more than 12.7 mm compared to the other relationships used in this study. ANOVA test revealed no significant impact of seasons or storm direction on error, but storm intensity correlated with higher errors. Locations farther from the radar tended to be underestimated, while higher elevations led to overestimations. A spatial analysis also revealed that storms that move north lead to more overestimations while storms headed south lead to more underestimations. The study recommends using unweighted Dual Z/R relationships for more precise precipitation estimates on a localized scale.

While the use of weather radars to continuously monitor the spatiotemporal dynamics of precipitation has grown in recent years, these systems are expensive and sparsely deployed across the world. In this context, densely located ground-based terminals for interactive satellite services have the potential for dual-use as weather sensors because they measure rain-attenuated power of the downlink signal. Although in the millimeter-wave regime, the rain rate has almost a linear relationship with specific attenuation, lack of other weather radar observables at satellite terminals imposes a daunting task of extracting rainfall rate from these highly attenuated signals. We address this problem by designing a deep convolutional neural network (CNN) that learns the relationship between the signal attenuation and rainfall rate observed by weather radars and rain gauges at a given location. During the prediction stage, the CNN accepts downlink attenuation as input and classifies the rain intensity which is then used to apply an appropriate rainfall estimator. Our experiments with real data show that, despite severe attenuation, CNN-based downlink rainfall accumulations closely follow the nearest C-band German weather service Deutscher Wetterdienst (DWD) radar.

While the use of weather radars to continuously monitor the spatiotemporal dynamics of precipitation has grown in recent years, these systems are expensive and sparsely deployed across the world. In this context, densely located ground-based terminals for interactive satellite services have the potential for dual-use as weather sensors because they measure rain-attenuated power of the downlink signal. Although in the millimeter-wave regime, the rain rate has almost a linear relationship with specific attenuation, lack of other weather radar observables at satellite terminals imposes a daunting task of extracting rainfall rate from these highly attenuated signals. We address this problem by designing a deep convolutional neural network (CNN) that learns the relationship between the signal attenuation and rainfall rate observed by weather radars and rain gauges at a given location. During the prediction stage, the CNN accepts downlink attenuation as input and classifies the rain intensity which is then used to apply an appropriate rainfall estimator. Our experiments with real data show that, despite severe attenuation, CNN-based downlink rainfall accumulations closely follow the nearest C-band German weather service Deutscher Wetterdienst (DWD) radar.

For tropical areas, rainfall is the main factor in the attenuation of millimeter wave transmission. This paper considers KLIA Sepang region of Malaysia as an example to measure and collect rainfall rate data via rain sensor, establish a mathematical model for millimeter wave rainfall attenuation in tropical areas, simulate and calculate rainfall attenuation at different frequency ranges of 20-300 GHz through MATLAB software, with emphasis on the analysis of millimeter wave communication attenuation characteristics in the widely used 30-50GHz frequency band. The results show that the greater the rainfall rate, the higher the frequency, and the greater the rainfall attenuation. Moreover, the vertical polarization achieves the lowest attenuation compared circular polarization and horizontal polarization. The attenuation and attenuation rate increase with the increase of frequency and rainfall rate. Specifically, the attenuation value appears linearly in the range of 15dB to 90dB in the rainfall rate of 20-60mm/h for the frequency bands of 30-50GHz.

For tropical areas, rainfall is the main factor in the attenuation of millimeter wave transmission. This paper considers KLIA Sepang region of Malaysia as an example to measure and collect rainfall rate data via rain sensor, establish a mathematical model for millimeter wave rainfall attenuation in tropical areas, simulate and calculate rainfall attenuation at different frequency ranges of 20-300 GHz through MATLAB software, with emphasis on the analysis of millimeter wave communication attenuation characteristics in the widely used 30-50GHz frequency band. The results show that the greater the rainfall rate, the higher the frequency, and the greater the rainfall attenuation. Moreover, the vertical polarization achieves the lowest attenuation compared circular polarization and horizontal polarization. The attenuation and attenuation rate increase with the increase of frequency and rainfall rate. Specifically, the attenuation value appears linearly in the range of 15dB to 90dB in the rainfall rate of 20-60mm/h for the frequency bands of 30-50GHz.

Estimating the magnitude of tropical cyclone (TC) rainfall at different landfalling states is an important aspect of the TC forecast that directly affects the level of response from emergency managers in coastal areas. This research analyses the spatial distribution of the rainfall magnitude in tropical cyclones (TCs) at different stages over global oceans. The research’s central hypothesis is that TC rainfall exhibits distinct features in the long-term satellite dataset due to the evolution of the spatial distribution, radial variation, and asymmetries at the stages before, during, and after landfall. The resulting patterns are analyzed through a statistical approach that takes advantage of a 20-year global satellite database of rainfall retrievals from the TRMM/GPM constellation, with the aim to achieve two main objectives: 1) The first objective was to explore the global trends of TC rainfall rates using observational evidence provided by a satellite-based climatology. Results indicate there is an increasing trend in the global average TC rainfall rate of about 1.3% per year, with a more pronounced trend in the northern hemisphere than in the southern hemisphere. 2) The second objective was to examine the spatial distribution of the magnitude and axisymmetric intensity profiles of rainfall over the six TC-prone basins. The obtained differences were quantitatively investigated in terms of geographic location, sub-regions within the storm, and TC intensities. Results indicate that major hurricanes in the Atlantic basin exhibit heavier inner-core rainfall rates than those in any other basins, and this difference is highly correlated to specific environmental conditions. Overall, with the achievement of the above-described objectives, this document identifies and summarizes the dominant factors that control rainfall distribution in global TCs, mainly focused on the differences during landfilling processes.

The increase in summer monsoon precipitation over western Africa during the last interglacial (LIG) relative to the pre-industrial (PI) is well documented, but it is uncertain whether this increase is due to larger rainfall rate alone, an extension of the summer monsoon season or a combination of the two. Due to different orbital config- uration, the boreal summer of the LIG was warmer but shorter than the PI, potentially influencing the summer monsoon duration. In this study, we employ a newly developed isotope-enabled climate model, AWI-ESM-wiso to investigate the intensity and length of the West African Summer Monsoon (WASM) for both LIG and PI time periods. Our model results indicate that, despite an intensification in summer insolation and an enhanced hydro-logical cycle, WASM season in the LIG is 9 days shorter compared to the PI. During the LIG, increased insolation in late spring and early summer strengthens the Saharan heat low (SHL) and its associated sub-systems, facilitating a faster accumulation of potential instability and an earlier WASM onset. However, a substantial earlier withdrawal of the WASM is also detected, driven by an earlier southward shift of insolation maximum. More- over, our findings are further supported by models participating in the 4th phase of the Paleoclimate Modelling Intercomparison Project (PMIP4).

The increase in summer monsoon precipitation over western Africa during the last interglacial (LIG) relative to the pre-industrial (PI) is well documented, but it is uncertain whether this increase is due to larger rainfall rate alone, an extension of the summer monsoon season or a combination of the two. Due to different orbital configuration, the boreal summer of the LIG was warmer but shorter than the PI, potentially influencing the summer monsoon duration. In this study, we employ a newly developed isotope-enabled climate model, AWI-ESM-wiso to investigate the intensity and length of the West African Summer Monsoon (WASM) for both LIG and PI time periods. Our model results indicate that, despite an intensification in summer insolation and an enhanced hydrological cycle, WASM season in the LIG is 9 days shorter compared to the PI. During the LIG, increased insolation in late spring and early summer strengthens the Saharan heat low (SHL) and its associated sub-systems, facilitating a faster accumulation of potential instability and an earlier WASM onset. However, a substantial earlier withdrawal of the WASM is also detected, driven by an earlier southward shift of insolation maximum. Moreover, our findings are further supported by models participating in the 4th phase of the Paleoclimate Modelling Intercomparison Project (PMIP4).

The pursuit for a weather monitoring system is critical for the measurement and observation of environmental parameters that are connected with human activities and habitation. In this study, a revolutionary weather monitoring system that uses a flexible graphical user interface (GUI) platform through a JAVA script software code is designed. The device is embedded with a ATMEGA 328P-PU microcontroller for the analysis of the signals from temperature, humidity, wind speed and rainfall rate sensor respectively. An analogue to digital converter initiates a signal conversion that enable GUI, to capture a reliable weather parameter at an interval of 10 minutes on a real time; through an ESP8266 Wi-Fi shield that creates a remote and host link between the sensors and the GUI. The developed system’s performance was evaluated by comparing results with available weather monitoring instruments. The developed system compared favourably with an available weather monitoring instrument with mean average accuracy of 99.96%, 99.41%, 99.96% and 99.26% in temperature, humidity, wind speed and rainfall rate respectively.

The pursuit for a weather monitoring system is critical for the measurement and observation of environmental parameters that are connected with human activities and habitation. In this study, a revolutionary weather monitoring system that uses a flexible graphical user interface (GUI) platform through a JAVA script software code is designed. The device is embedded with a ATMEGA 328P-PU microcontroller for the analysis of the signals from temperature, humidity, wind speed and rainfall rate sensor respectively. An analogue to digital converter initiates a signal conversion that enable GUI, to capture a reliable weather parameter at an interval of 10 minutes on a real time; through an ESP8266 Wi-Fi shield that creates a remote and host link between the sensors and the GUI. The developed system’s performance was evaluated by comparing results with available weather monitoring instruments. The developed system compared favourably with an available weather monitoring instrument with mean average accuracy of 99.96%, 99.41%, 99.96% and 99.26% in temperature, humidity, wind speed and rainfall rate respectively.

The pursuit for a weather monitoring system is critical for the measurement and observation of environmental parameters that are connected with human activities and habitation. In this study, a revolutionary weather monitoring system that uses a flexible graphical user interface (GUI) platform through a JAVA script software code is designed. The device is embedded with a ATMEGA 328P-PU microcontroller for the analysis of the signals from temperature, humidity, wind speed and rainfall rate sensor respectively. An analogue to digital converter initiates a signal conversion that enable GUI, to capture a reliable weather parameter at an interval of 10 minutes on a real time; through an ESP8266 Wi-Fi shield that creates a remote and host link between the sensors and the GUI. The developed system’s performance was evaluated by comparing results with available weather monitoring instruments. The developed system compared favourably with an available weather monitoring instrument with mean average accuracy of 99.96%, 99.41%, 99.96% and 99.26% in temperature, humidity, wind speed and rainfall rate respectively.

The pursuit for a weather monitoring system is critical for the measurement and observation of environmental parameters that are connected with human activities and habitation. In this study, a revolutionary weather monitoring system that uses a flexible graphical user interface (GUI) platform through a JAVA script software code is designed. The device is embedded with a ATMEGA 328P-PU microcontroller for the analysis of the signals from temperature, humidity, wind speed and rainfall rate sensor respectively. An analogue to digital converter initiates a signal conversion that enable GUI, to capture a reliable weather parameter at an interval of 10 minutes on a real time; through an ESP8266 Wi-Fi shield that creates a remote and host link between the sensors and the GUI. The developed system’s performance was evaluated by comparing results with available weather monitoring instruments. The developed system compared favourably with an available weather monitoring instrument with mean average accuracy of 99.96%, 99.41%, 99.96% and 99.26% in temperature, humidity, wind speed and rainfall rate respectively.

The pursuit for a weather monitoring system is critical for the measurement and observation of environmental parameters that are connected with human activities and habitation. In this study, a revolutionary weather monitoring system that uses a flexible graphical user interface (GUI) platform through a JAVA script software code is designed. The device is embedded with a ATMEGA 328P-PU microcontroller for the analysis of the signals from temperature, humidity, wind speed and rainfall rate sensor respectively. An analogue to digital converter initiates a signal conversion that enable GUI, to capture a reliable weather parameter at an interval of 10 minutes on a real time; through an ESP8266 Wi-Fi shield that creates a remote and host link between the sensors and the GUI. The developed system’s performance was evaluated by comparing results with available weather monitoring instruments. The developed system compared favourably with an available weather monitoring instrument with mean average accuracy of 99.96%, 99.41%, 99.96% and 99.26% in temperature, humidity, wind speed and rainfall rate respectively.