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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.

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

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/)

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.

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.

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

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.

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.

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 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.

Tropical cyclones (TC)s are a major natural hazard and the jet stream is closely linked to mid-latitude storm activity. Both TCs and the jet stream can therefore have a significant impact on society, yet the extent to which ocean variability impacts on TCs and the jet stream is far from understood. This thesis aims to improve understanding of when and how the ocean modulates storm activity. The emphasis is on how airsea interactions and variability of the Atlantic Ocean circulation impact on the frequency and intensity of tropical cyclones, together with the ocean influence on the northern hemisphere jet stream. Ocean drivers of recent active Atlantic hurricane seasons are found to take two forms: late winter changes in the ocean circulation related to a reduced Atlantic Meridional Overturning Circulation and late spring/early summer changes in the airsea heat flux. Over the Atlantic, the TC rainfall rate (mm/hr) increases by 6% for a 1°C SST rise in the Main Development Region (MDR). Over land, however, the rainfall rate increases by over 30% for a 1°C rise in SST in the MDR and appears linked mainly to the increase in TC wind speed. In the subtropical Atlantic, around Bermuda, average TC intensity is found to be increasing at 5kts per decade linked to rising ocean temperatures in the region. The prediction of TC potential intensity is also found to be closer to actual intensity using the average temperature through the top 50m layer (!"#$ %%%%%%) as opposed to SST, with the improvement proportional to the SST - !"#$ %%%%%% temperature difference. For the northern hemisphere jet stream, the ocean acts to reduce the seasonal range of jet latitude variability, particularly over the North Atlantic where the oceanic Meridional Heat Transport (MHT) is greatest. Interannual to decadal variability in jet latitude and speed is most evident in the North Pacific in winter where the Pacific Decadal Oscillation explains 50% of the variance in jet latitude since 1940. On multid

This work investigates the impact of rain on the power production of a wind turbine, including structural flexibility effects. Wind turbines are subjected to numerous conditions, including the change of weather, such as snow, hail and rain. In the available literature, the main focus has been given to the effects of snow rather than rain. In this study, a strong one–way fluid–structure interaction (FSI) approach was utilised to investigate the interconnected characteristics of the fluid and structural domains. The Reynolds-averaged Navier–Stokes (RANS) approach incorporated with multiple reference frame (MRF), discrete phase modelling (DPM) and wall–film model were used to investigate the aerodynamic behaviour of the selected geometries. The NACA 0012 and S809 aerofoils were used as the validation test cases, and then similar methodology was applied for the NREL Phase VI wind turbine. The structural response of the wind turbine was accounted by a three dimensional finite element method (FEM) utilising the shell theory. Parametric studies are included in this work to analyse the effect of rain characteristics towards the surrounding airflow. It was found that the presence of rain negatively affected the aerodynamics of these selected geometries, measured in terms of lift, drag and torque production. For the NREL Phase VI wind turbine, a maximum torque reduction by 19.97% was obtained when the freestream velocity was varied. The aerodynamic penalties were more evident by increasing the rainfall rate up to 18.0% drop of torque respectively from rainfall rate of 3.75 g/m3 to 30.0 g/m3. Nonetheless, higher torque production was found for larger raindrop diameter. An increase by 11.27% of torque was observed when the diameter is increased from 3 mm to 6 mm. In terms of structural response, the thrust showed a dominant influence. Additionally, the amount of the total deformation was dominated by the z deformation in the direction of the thrust. The blades deflections were

Tropical cyclones (TC)s are a major natural hazard and the jet stream is closely linked to mid-latitude storm activity. Both TCs and the jet stream can therefore have a significant impact on society, yet the extent to which ocean variability impacts on TCs and the jet stream is far from understood. This thesis aims to improve understanding of when and how the ocean modulates storm activity. The emphasis is on how airsea interactions and variability of the Atlantic Ocean circulation impact on the frequency and intensity of tropical cyclones, together with the ocean influence on the northern hemisphere jet stream. Ocean drivers of recent active Atlantic hurricane seasons are found to take two forms: late winter changes in the ocean circulation related to a reduced Atlantic Meridional Overturning Circulation and late spring/early summer changes in the airsea heat flux. Over the Atlantic, the TC rainfall rate (mm/hr) increases by 6% for a 1°C SST rise in the Main Development Region (MDR). Over land, however, the rainfall rate increases by over 30% for a 1°C rise in SST in the MDR and appears linked mainly to the increase in TC wind speed. In the subtropical Atlantic, around Bermuda, average TC intensity is found to be increasing at 5kts per decade linked to rising ocean temperatures in the region. The prediction of TC potential intensity is also found to be closer to actual intensity using the average temperature through the top 50m layer (!"#$ %%%%%%) as opposed to SST, with the improvement proportional to the SST - !"#$ %%%%%% temperature difference. For the northern hemisphere jet stream, the ocean acts to reduce the seasonal range of jet latitude variability, particularly over the North Atlantic where the oceanic Meridional Heat Transport (MHT) is greatest. Interannual to decadal variability in jet latitude and speed is most evident in the North Pacific in winter where the Pacific Decadal Oscillation explains 50% of the variance in jet latitude since 1940. On multid

Robust sensing and perception in adverse weather conditions remain one of the biggest challenges for realizing reliable autonomous vehicle mobility services. Prior work has established that rainfall rate is a useful measure for the adversity of atmospheric weather conditions. This work presents a probabilistic hierarchical Bayesian model that infers rainfall rate from automotive lidar point cloud sequences with high accuracy and reliability. The model is a hierarchical mixture of experts model, or a probabilistic decision tree, with gating and expert nodes consisting of variational logistic and linear regression models. Experimental data used to train and evaluate the model is collected in a large-scale rainfall experiment facility from both stationary and moving vehicle platforms. The results show prediction accuracy comparable to the measurement resolution of a disdrometer, and the soundness and usefulness of the uncertainty estimation. The model achieves RMSE 2.42\,mm/h after filtering out uncertain predictions. The error is comparable to the mean rainfall rate change of 3.5\,mm/h between measurements. Model parameter studies show how predictive performance changes with tree depth, sampling duration, and crop box dimension. A second experiment demonstrates the predictability of higher rainfall above 300\,mm/h using a different lidar sensor, demonstrating sensor independence., Comment: Accepted for IEEE IV 2022

To retrieve the gamma drop size distribution (DSD) parameters from observed drop spectra, the most common approach is the method of moments (MM). However, the goodness of this method is still disputed. To assess its reliability, the aims of this paper are: (i) estimation of empirical values of rainfall rate (I) and kinetic energy (KE) from DSD measurements collected by a laser-optical disdrometer; (ii) estimation of gamma DSD parameters by MM and another widespread method, i.e. maximum likelihood (ML); (iii) evaluation of theoretical values of rainfall rate and KE and comparison between these values and measured ones. The novelty of this work is the assessment of both MM and ML using the rainfall intensity measured by the disdrometer as a benchmark, rather than the KE or a statistical test as done in common practice. The assessment of the goodness of the estimates was performed on variables most investigated in soil erosion studies (i.e.Iand KE). Results show that smaller error values are associated with ML and that MM does not provide reliable estimations ofI.On the other hand, both methods substantially underestimate KE with increasing rainfall intensity. (c) 2020 John Wiley & Sons, Ltd.

Future cellular systems are expected to use millimeter-wave (mm-Wave) frequency bands in addition to the existing microwave bands under 6 GHz. Severe weather conditions, including sand and dust storms (SDSs) and heavy rainfalls, challenge reliable communications over wireless links at those higher frequencies. In such conditions, besides frequency-dependent path-loss, radio signals experience additional attenuation. The SDS attenuation is related to visibility, receiver distance to the storm origin point, soil type, frequency, temperature and humidity. On the other hand, the rainfall attenuation is affected by rainfall rate, polarization, carrier frequency, temperature and raindrop size distribution. Leveraging on experimental measurements carried out in previous works, a novel unified mathematical framework is introduced in this paper to include SDS/rainfall-dependent attenuation in the performance evaluation of terrestrial wireless cellular networks in terms of coverage probability, bit error rate (BER) and achievable rate in the mm-Wave band. Extensive numerical results are presented to show the effects of the different SDS/rainfall parameters on performance, showing that the degradation due to SDS is generally higher than that due to rain and may cause a reduction of even six orders of magnitude in the average achievable bit rate when the frequency increases from 28 to 38 GHz.

Future cellular systems are expected to use millimeter-wave (mm-Wave) frequency bands in addition to the existing microwave bands under 6 GHz. Severe weather conditions, including sand and dust storms (SDSs) and heavy rainfalls, challenge reliable communications over wireless links at those higher frequencies. In such conditions, besides frequency-dependent path-loss, radio signals experience additional attenuation. The SDS attenuation is related to visibility, receiver distance to the storm origin point, soil type, frequency, temperature and humidity. On the other hand, the rainfall attenuation is affected by rainfall rate, polarization, carrier frequency, temperature and raindrop size distribution. Leveraging on experimental measurements carried out in previous works, a novel unified mathematical framework is introduced in this paper to include SDS/rainfall-dependent attenuation in the performance evaluation of terrestrial wireless cellular networks in terms of coverage probability, bit error rate (BER) and achievable rate in the mm-Wave band. Extensive numerical results are presented to show the effects of the different SDS/rainfall parameters on performance, showing that the degradation due to SDS is generally higher than that due to rain and may cause a reduction of even six orders of magnitude in the average achievable bit rate when the frequency increases from 28 to 38 GHz.

Ammonia is one of the most impactful pollutants emitted from agricultural activities, harming human health and contributing to biodiversity loss. In ammonia emission inventories, the spatial distribution of annual emissions is mostly approximated by constant empirical emission fractions, which do not account for spatial variability, nor for temporal variability within a year or between years caused by weather variations. Besides, factors like manure properties, soil properties, and manure application techniques also lead to differences in the amount of ammonia emitted into the atmosphere. By not or only partly accounting for these factors, significant uncertainties are introduced into ammonia emission estimates at regional and national scales. In this study, we applied the empirical ALFAM2 model to derive spatially explicit slurry application emission fractions from cropland for use in the large-scale INTEGRATOR model, using the information on slurry properties (dry matter content and pH), manure application rate, application technique, incorporation time, air temperature, wind speed, and rainfall rate. In addition, the impact of weather on the ammonia emissions from animal housing and manure storage systems was included through a temperature-dependent scaling. We applied the method to investigate the year-to-year spatio-temporal variabilities of ammonia emissions and modeled concentrations across Germany from 2015 to 2018. Through the comparison with in situ measurements and satellite-derived observations, we studied how surface concentrations and total columns relate to local meteorology. We found that the spatio-temporal variability in emission fractions improves the ability to reproduce the interannual variability observed in ammonia concentration and total column measurements. This study shows that the developed approach to derive spatially explicit emission fractions can significantly improve ammonia emission modeling and is of great importance for studying th

Previous studies on convective precipitation forecasting in South China have focused on the effects of multiscale dynamics and microphysics parameterizations. However, limited investigation has been conducted on how uncertainty in aerosol data might cause errors in quantitative precipitation forecast for South China's coastal convection. In this case study, we evaluated the impact of aerosol uncertainties on South China's severe coastal convection using convection-permitting simulations. We estimated the variability range of aerosol concentrations with observations for the pre-summer months. The simulation results suggest that the rainfall pattern and intensity change notably when aerosol concentrations are varied. Decreasing the concentration of water-friendly (WF) aerosols intensifies precipitation through reduced cloud water number concentration and increased droplet size. Increasing the concentration of ice-friendly (IF) aerosols results in up to 40% increase in vertical velocity and latent heat compared to minimal IF aerosol condition, by enhancing the heterogeneous process and dynamically intensifying convection. Consequently, the simulation with minimal WF and maximal IF aerosol concentrations shows prolonged intense precipitation over the entire life cycle of convection. However, when both WF and IF aerosols are set to minimal concentrations, the simulation produces the maximum peak rainfall rate, which is about 50% stronger than the simulation with the climatological mean concentration, due to an enhanced homogeneous process that results in a higher ice concentration and more efficient ice-phase precipitation growth. Meanwhile, variation in aerosol concentration affects convection initiation (CI), with a lower concentration of WF aerosol inducing earlier CI onset. Decreasing hygroscopicity leads to higher precipitation.

Hurricane Irene (2011) was a category 3 tropical storm that resulted in severe flooding, causing at least 40 deaths and more than $15 billion in damaged property along the US northeastern seaboard (Avila and Cangialosi, 2011). This work analyzes the sensitivity of numerical simulations of this devastating storm to the physical parameterizations in the Weather Research and Forecasting (WRF) model and a coupled modeling framework (WRF and the Regional Ocean Modeling System). Simulations were conducted in two 16-member physics ensembles, each included two radiation schemes, two cumulus schemes, two microphysics schemes, and two planetary boundary layer schemes. The simulations were evaluated primarily on the accuracy of the simulated track and the intensity of the storm compared to observations over a period of 5 days centered on the storm's maximum intensity. Cumulus and planetary boundary layer parameterizations were the most influential physics schemes with radiation and microphysics having much smaller effects. The simulated track, intensity, translational speed, and rainfall rate were particularly sensitive to cumulus schemes given the differences in representation of shallow convection. Tracks and rainfall rates also showed sensitivity to the inclusion or exclusion of local effects in the parameterization of planetary boundary layer processes. Using a grid spacing of 12 km, coupling an ocean model to WRF affected the storm track (with increased sensitivity to the cumulus scheme selected) and translational speed, but had very little effect on the rainfall rate or intensity of the storm. In terms of track accuracy, the optimal combination of physics parameterizations for WRF is not necessarily optimal for the coupled WRF-ROMS system.

Drainage networks link erosional landscapes and sedimentary basins in a source-to-sink system, controlling the spatial and temporal distribution of sediment flux at the outlets. Variations of accumulation rates in a sedimentary basin have been classically interpreted as changes in erosion rates driven by tectonics and/or climate. We studied the interactions between deformation, rainfall rate and the intrinsic dynamics of drainage basins in an experimental fold-and-thrust belt subjected to erosion and sedimentation under constant rainfall and shortening rates. The emergence of thrust sheets at the front of a prism may divert antecedent transverse channels (perpendicular to the structural grain) leading to the formation of longitudinal reaches, later uplifted and incorporated in the prism by the ongoing deformation. In the experiments, transverse incisions appear in the external slopes of the emerging thrust sheets. Headward erosion in these transverse channels results in divide migration and capture of the uplifted longitudinal channels located in the inner parts of the prism, leading to drainage network reorganization and modification of the sediment routing system. We show that the rate of drainage reorganization increases with the rainfall rate. It also increases in a nonlinear way with the rate of uplift. We explain this behaviour by an exponent > 1 on the slope variable in the framework of the stream power erosion model. Our results confirm the view that early longitudinal-dominated networks are progressively replaced by transverse-dominated rivers during mountain building. We show that drainage network dynamics modulate the distribution of sedimentary fluxes at the outlets of experimental wedges. We propose that under constant shortening and rainfall rates the drainage network reorganization can also modulate the composition and the spatial distribution of clastic fluxes in foreland basins. © 2018 The Authors. Basin Research © 2018 John Wiley & Sons Ltd, Europe

Hurricane Irene (2011) was a category 3 tropical storm that resulted in severe flooding, causing at least 40 deaths and more than $15 billion in damaged property along the US northeastern seaboard (Avila and Cangialosi, 2011). This work analyzes the sensitivity of numerical simulations of this devastating storm to the physical parameterizations in the Weather Research and Forecasting (WRF) model and a coupled modeling framework (WRF and the Regional Ocean Modeling System). Simulations were conducted in two 16-member physics ensembles, each included two radiation schemes, two cumulus schemes, two microphysics schemes, and two planetary boundary layer schemes. The simulations were evaluated primarily on the accuracy of the simulated track and the intensity of the storm compared to observations over a period of 5 days centered on the storm's maximum intensity. Cumulus and planetary boundary layer parameterizations were the most influential physics schemes with radiation and microphysics having much smaller effects. The simulated track, intensity, translational speed, and rainfall rate were particularly sensitive to cumulus schemes given the differences in representation of shallow convection. Tracks and rainfall rates also showed sensitivity to the inclusion or exclusion of local effects in the parameterization of planetary boundary layer processes. Using a grid spacing of 12 km, coupling an ocean model to WRF affected the storm track (with increased sensitivity to the cumulus scheme selected) and translational speed, but had very little effect on the rainfall rate or intensity of the storm. In terms of track accuracy, the optimal combination of physics parameterizations for WRF is not necessarily optimal for the coupled WRF-ROMS system

Climate change is one of the biggest threats for the new millennium, and Bangladesh is considered as "Poster Child" as an impact on climate change in the world. The main focus of this study is to investigate the changing pattern of climate parameters, particularly temperature, rainfall, humidity, cloud coverage, and wind speed in two coastal islands of the southeastern coast of Bangladesh from 1977 to 2017. The linear regression model described that the temperature in Kutubdia and Sandwip islands was 0.0298 and 0.0444 times increased from 1977 to 2017. Besides, rainfall patterns in Kutubdia decreased by 0.4083, and Sandwip Islands increased by 0.875 every year from its previous counterpart. The humidity level also increased due to the rise of temperature and water availability for evaporation from irrigation. Moreover, significant changes in wind speed and the cloud coverage rate in the Island areas increased with the increasing value of temperature and humidity. It also means the rainfall rate increases with cloud cover in the sky. However, the study found decreasing rates of bright sunshine in the Island areas. The declining rate of sunshine is very high and is a matter of great concern for the agriculture and health sectors in particular areas. Therefore, the community's concept of climate parameters, association, and extremes is well apparent. Identify poor land use planning as the primary anthropogenic driver of the change, and they advocated boosting the capacity of linked fields that are in danger owing to climate change. To conclude, the coastal inhabitants recommended that taking preparedness would be easier if the information transmitted through quicker and reliable sources such as news broadcasts, phone messages, or the internet.

Saudi Arabia is seeking fresh groundwater resources to face the increase in anthropogenic activities. The groundwater storage variations and occurrence were investigated and the surface and subsurface structures influencing the groundwater resources in the research area were defined using a combined study of Gravity Recovery and Climate Experiment, aeromagnetic data, and electrical resistivity data with other relevant datasets. Results are: The groundwater storage fluctuation is calculated at −0.34 ± 0.01 mm/yr during the period 04/2002-12/2021. The area is receiving an average annual rainfall rate of 117.6 mm during the period 2002 to 2019. Three structural trends, defined in the directions of NS, NNW, and NNE are cutting the sedimentary cover and the basement rocks. The sedimentary cover ranges from 0 to 1.2 km thick. Vertical electrical sounding results indicate three main geoelectric layers: the surface geoelectrical layer of higher resistivity values (428-9626 Ω. m) is made up of unconsolidated Quaternary sediments; the water-bearing layer of saturated sands with a resistivity range between 5.1 and 153 Ω. m and with depths vary from 1 to 94 m, and highly fractured basement rocks with resistivity values ranging from 813 to 6030 Ω. m. The integrated results are useful in providing a comprehensive image of the study area’s surface and subsurface structures, as well as groundwater potential in the southwestern part of Saudi Arabia. Our integrated approach provides a reproducible model for assessing groundwater potential in arid and semiarid areas., Water Resources

Atmospheric aerosol particle concentrations are strongly affected by various wet processes, including below and in-cloud wet scavenging and in-cloud aqueous-phase oxidation. We studied how wet scavenging and cloud processes affect particle concentrations and composition during transport to a rural boreal forest site in northern Europe. For this investigation, we employed air mass history analysis and observational data. Long-term particle number size distribution (∼15 years) and composition measurements (∼8 years) were combined with air mass trajectories with relevant variables from reanalysis data. Some such variables were rainfall rate, relative humidity, and mixing layer height. Additional observational datasets, such as temperature and trace gases, helped further evaluate wet processes along trajectories with mixed effects models. All chemical species investigated (sulfate, black carbon, and organics) exponentially decreased in particle mass concentration as a function of accumulated precipitation along the air mass route. In sulfate (SO4) aerosols, clear seasonal differences in wet removal emerged, whereas organics (Org) and equivalent black carbon (eBC) exhibited only minor differences. The removal efficiency varied slightly among the different reanalysis datasets (ERA-Interim and Global Data Assimilation System; GDAS) used for the trajectory calculations due to the difference in the average occurrence of precipitation events along the air mass trajectories between the reanalysis datasets. Aqueous-phase processes were investigated by using a proxy for air masses travelling inside clouds. We compared air masses with no experience of approximated in-cloud conditions or precipitation during the past 24 h to air masses recently inside non-precipitating clouds before they entered SMEAR II (Station for Measuring Ecosystem–Atmosphere Relations). Significant increases in SO4 mass concentration were observed for the latter air masses (recently experienced non-precipita

With an intensification of heavy rain events in a changing climate and a rapid urbanization the risk for pluvial flooding is increasing in our societies. Pluvial flooding, which is formed when the rainfall rate exceeds the infiltration or drainage rate, can occur rapidly and cause great damages, large economic losses and possibly risk human lives. This kind of flooding is difficult to predict since it is caused by short-term and often local processes, but preventive measures and more robust infrastructure developed over the last decades have decreased the risk of the most severe damages. One way to prevent damage is to map risk areas and take measures by performing a cloudburst modelling, which can be done as a 2D hydraulic modelling. Common practice in cloudburst modelling today is to use a uniform design storm, often the Chicago Design Storm (CDS), with the same hyetograph applied evenly over the whole model area. Even though rain is not spatially uniform this assumption might be valid for more stratiform frontal rain. Intense rain events however have a higher spatial variation in rain intensity, and an assumption like this might significantly affect the results. This study aimed to investigate the effect of the spatial variation in rain intensity on the modelled hydraulic response from an intense rain event. It was performed through a case study of the cloudburst in Gävle, Sweden, in August 2021. A 2D hydraulic model of the city was prepared in the software MIKE 21 Flow Model FM and the cloudburst event was simulated with a spatially varied rainfall input, based on radar data from the event with a 2x2 km resolution, and with spatially uniform rainfall input both with the temporal variation in rain intensity from the event and with a Chicago Design Storm, all with the same total volume. The scenarios were evaluated in terms of proportion of the model area being flooded, the average maximum flooding depth and by mapping the difference in flooding depth over the who, Med en intensifiering av häftiga regnväder i ett förändrat klimat och en allt snabbare urbanisering ökar risken för pluviala översvämningar i våra samhällen. Pluviala översvämningar, som skapas av att regnintensiteten är högre än infiltrations- eller dräneringshastigheten, kan uppstå plötsligt och orsaka stora skador, ekonomiska förluster och även i värsta fall riskera människoliv. Denna typ av översvämning är svår att förutse eftersom den orsakas av snabba och ofta lokala processer, men förebyggande åtgärder och mer robust infrastruktur som har utvecklats de senaste decennierna har minskat risken för de allvarligaste skadorna. Ett sätt att förebygga skador är att kartera riskområden genom skyfallsmodellering, till exempel med en tvådimensionell hydraulisk modell. Praxis idag är att använda spatialt uniforma typregn vid skyfallsmodellering, där samma hyetograf appliceras jämnt över hela modellområdet. Detta antagande kan ge giltiga resultat för mer stratiforma frontregn, men intensiva regn, skyfall, har generellt sett en hög spatial variation i intensiteten vilket gör att antagandet skulle kunna påverka resultatet signifikant. Denna studie syftade till att undersöka effekten av den spatiala variationen i regnintensitet på den simulerade hydrauliska responsen från ett intensivt regn och den utfördes som en fallstudie av skyfallet i Gävle 17-18 augusti 2021. En 2D hydraulisk modell av Gävle förbereddes i programmet MIKE 21 Flow Model FM och simuleringar utfördes med en spatialt varierad regnindata, baserad på radardata från tillfället med en 2x2 km upplösning, och med spatialt uniforma regnindata både med den verkliga tidsvariationen och med en Chicago Design Storm (CDS), alla med samma totala volym. Skillnaden mellan scenarierna utvärderades genom att jämföra andel översvämmat modellområde, medel av maximala översvämningsdjupet och en kartering av skillnaden i översvämningsdjup över hela modellområdet. Resultaten visade att den spatiala variationen i regnindatan hade

Plastic debris has become an acute marine pollution concern worldwide in modern times. Indonesia is particularly impacted because of its high population density, heavy rainfall rate and numerous coastlines. A Lagrangian analysis was performed to simulate the fate of fictive marine debris drifting along surface currents, including tides and Stokes drift. The fictive particles were released according to the discharge rate of 21 Indonesian rivers and advected over 4 years. Most of the particles were stranded along Indonesian coasts (60%), before 6 months had elapsed (84%) and within a range of 1000 km (76%). The time variability exhibited two seasonal peaks, one centered on January-February and one on June-July, consistent with in situ observations. However, the results underline the complexity of performing direct comparisons between in situ observations and numerical simulations for stranded waste due to limited measurements and the heterogeneity of field methods and protocols.

A methodology to process radar wind profiler Doppler spectra is presented and implemented for an UHF Degreane PCL1300 system. First, double peak signal detection is conducted at each height level and, then, vertical continuity checks for each radar beam ensure physically consistent measurements. Second, horizontal and vertical wind, kinetic energy flux components, Doppler moments, and different precipitation-related variables are computed. The latter include a new precipitation type estimate, which considers rain, snow, and mixed types, and, finally, specific variables for liquid precipitation, including drop size distribution parameters, liquid water content and rainfall rate. The methodology is illustrated with a 48 h precipitation event, recorded during the Cerdanya-2017 field campaign, carried out in the Eastern Pyrenees. Verification is performed with a previously existing process for wind profiler data regarding wind components, plus precipitation estimates derived from Micro Rain Radar and disdrometer observations. The results indicated that the new methodology produced comparable estimates of wind components to the previous methodology (Bias < 0.1 m/s, RMSE ˜ 1.1 m/s), and was skilled in determining precipitation type when comparing the lowest estimate of disdrometer data for snow and rain, but did not correctly identify mixed precipitation cases. The proposed methodology, called UBWPP, is available at the GitHub repository., Peer Reviewed, Postprint (published version)

GNSS meteorology is today one of the most growing technologies to monitor severe weather events. In this paper, we present the usage of 160 GPS reference stations over the period of 14 days to monitor and track Hurricane Harvey, which struck Texas in August 2017. We estimate the Zenith Wet Delay (ZWD) and the tropospheric gradients with 30 s interval using TOMION v2 software and carry out the processing in Precise Point Positioning (PPP) mode. We study the relationship of these parameters with atmospheric variables extracted from Tropical Rainfall Measuring Mission (TRMM) satellite mission and climate reanalysis model ERA5. This research finds that the ZWD shows patterns related to the rainfall rate and to the location of the hurricane. We also find that the tropospheric gradients are correlated with water vapor gradients before and after the hurricane, and with the wind and the pressure gradients only after the hurricane. This study also shows a new finding regarding the spectral distribution of the gradients, with a clear diurnal period present, which is also found on the ZWD itself. This kind of study approaches the GNSS meteorology to the increasing requirements of meteorologist in terms of monitoring severe weather events., Peer Reviewed, Postprint (published version)

In convergent systems, the interplay between tectonics, erosion, and sedimentation controls the orogenic evolution. The nature of the interactions between these factors is still elusive due to the complex feedbacks that operate across different temporal and spatial scales. Here, we investigate these feedbacks with analog models of landscape evolution designed to account for both tectonic forcing and surface processes, using a water-saturated granular material that allows to simulate contemporary brittle deformation and surface processes. The deformation is imposed by the movement of a rigid backstop, and surface processes are triggered by simulated rainfall and runoff. We vary the convergence velocity, rainfall rate, and basal angle of the box, testing how different boundary conditions affect the balance between tectonics and surface processes. We measure the competition between input fluxes (tectonics) and output fluxes (erosion) of material, showing how sedimentation strongly affects the balance between these fluxes. The results suggest that the experimental equilibrium between tectonics and erosion can be achieved, in the analog models, only for low convergence rates (about 10 mm hr−1) and/or for high basal angle (>2°, limited sedimentation). If the foreland is overfilled with sediments and/or if convergence velocity is higher, channels decrease their erosional efficiency, moving the dynamic equilibrium between tectonics and erosion toward the former.

An effective filtering technique is required for rainfall rate measurement by weather radar. A Jensen–Shannon distance (JSD)-based thresholding filter is proposed to mitigate nonmeteorological signals, either in clear air or rain situations. This algorithm classifies range-Doppler bins into two classes, hydrometeors and nonhydrometeors, based on spectral polarimetric variable features. The result is a mask to be applied on the spectrograms. The variable selected here is the spectral co-polar correlation coefficient, available in dual-polarization and full polarimetric radars. The algorithm first does global thresholding by finding an optimized threshold value based on the averaged clear-air spectral polarimetric variable distribution. Next, classical filtering steps are carried out like a ground clutter notch filter around 0 ms−1, a mathematical morphology to fill gaps in the hydrometeor areas, and a removal of narrow Doppler power spectra. The second part of this article is the assessment of filtering techniques without ground truth. An assessment without ground truth is useful to select optimal algorithm configurations from a large solution space. Criteria of good filtering are defined both in the spectral and time domain. Based on those criteria, subjective and objective unsupervised evaluation metrics are derived, with a focus on the objective ones. Data, including clear air and rain collected from a full polarimetric Doppler X-band radar in the urban area, are used. With the proposed unsupervised evaluation metrics, the JSD-based thresholding filter is compared to two spectral polarimetric filters. Overall, the JSD-based filter performs very well considering both the subjective and the objective evaluation metrics., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Atmospheric Remote Sensing, Microwave Sensing, Signals & Systems