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The IMERG data product is an optimal combination of precipitation estimates from the Global Precipitation Mission (GPM), making use of a variety of data types, primarily data from various spaceborne passive instruments. Previous versions of the IMERG product have been extensively validated by comparisons with gauge data and ground-based radars over land. However, IMERG rain rates, especially sub-daily, over open ocean are less validated due to the scarcity of comparison data, particularly with the relatively new Version 07. To address this issue, we consider IMERG V07 30-min data acquired in tropical cyclones over open ocean. We perform two tasks. The first is a straightforward comparison between IMERG precipitation rates and those retrieved from the GPM Dual-frequency Precipitation Radar (DPR). From this, we find that IMERG and DPR are close at low rain rates, while, at high rain rates, IMERG tends to be lower than DPR. The second task is the assessment of IMERG's ability to represent or detect structures commonly seen in tropical cyclones, including the annular structure and concentric eyewalls. For this, we operate on IMERG data with many machine learning algorithms and are able to achieve a 96% classification accuracy, indicating that IMERG does indeed contain TC structural information. [ABSTRACT FROM AUTHOR]

Rain-induced attenuation serves as a substantial factor influencing link power sizing in both terrestrial and satellite-based applications. The absence of in-situ rain rate measurements for localized link designs has led to generalized assumptions about rain-induced attenuation, contributing to increased instances of signal impairments during rainfall events. This study addresses this challenge by quantifying rain rate statistics over country capitals in Western and Central Africa. The Chebil and Moupfouma models were employed to estimate essential rain rate statistics, including the point rainfall rate R0.01, utilizing a 32-year data set of CRU rainfall accumulations. The results provide accurate rain-based statistics crucial for predicting, planning, and designing satellite and terrestrial links, especially for various microwave (MW) and millimeter-wave (mmW) technologies in specific locations. These rain rate insights are invaluable for engineers and designers working on communication systems, offering a comprehensive resource to enhance the accuracy of link budgeting and develop effective strategies for mitigating the impact of rainfall on signal quality. This research contributes to the optimization of communication systems, ensuring robust performance across diverse atmospheric conditions. [ABSTRACT FROM AUTHOR]

Spaceborne synthetic aperture radar (SAR) is gradually being applied to hurricane observation because of its all-weather, high-resolution observation capability. In particular, the retrieval of rain rate using SAR images holds significant scientific and practical importance. However, accurately retrieving rain rate over the sea surface, particularly for high rain rate events under hurricane conditions, remains a significant challenge. The study proposes a new method for rain rate retrieval from hurricane SAR images. We have developed a cascaded feedforward neural network model based on Sentinel-1’s double-polarized C-band SAR images of 46 hurricanes to retrieve rain rate under hurricane conditions. In order to overcome the problem of local optimal solution of neural network, the genetic algorithm is employed for optimized model parameter selection. Preliminary results indicate that this approach not only enhances the neural network's iteration speed but also improves its prediction accuracy. Compared with the rain rate of the Stepped-Frequency microwave radiometers, the root mean squared error of retrieved rain rate is 3.05 mm/h and the correlation coefficient is 0.88. Furthermore, we independently verify the rain rate during Hurricane Douglas and compared with global precipitation mission 2-level dual-frequency precipitation radar rain rate product, the results demonstrate that our model can effectively retrieve rain rate in the range of 0–60 mm/h under hurricane conditions. The encouraging results prove the feasibility of the method in SAR rain rate retrieval.

Precipitation plays an important role in cloud and aerosol processes over the Southern Ocean (SO). The main objective of this study is to characterize SO precipitation properties associated with SO stratocumulus clouds. We use data from the Southern Ocean Clouds Radiation Aerosol Transport Experimental Study (SOCRATES), and leverage observations from airborne radar, lidar, and in situ probes. We find that for the cold‐topped clouds (cloud‐top‐temperature <0°C), the phase of precipitation with reflectivity >0 dBZ is predominantly ice, while reflectivity < −10 dBZ is predominantly liquid. Liquid‐phase precipitation properties are retrieved where radar and lidar are zenith‐pointing. Power‐law relationships between reflectivity (Z) and rain rate (R) are developed, and the derived Z–R relationships show vertical dependence and sensitivity to the presence of droplets with diameters between 10 and 40 μm. Using derived Z–R relationships, a reflectivity‐velocity (ZV) retrieval method, and a radar‐lidar retrieval method, we derive rain rate and other precipitation properties. The retrieved rain rate from all three methods shows good agreement with in‐situ aircraft estimates, with rain rates typically being quite light (<0.1 mm hr−1). We examine the vertical distribution of precipitation properties, and find that rain rate, precipitation number concentration, and precipitation liquid water all decrease as one gets closer to the surface, while precipitation size and distribution width increases. We also examine how cloud base rain rate (RCB) depends on cloud depth (H) and aerosol concentration (Na) for particles with a diameter greater than 70 nm, and find that RCB is proportional to H3.1Na−0.8 ${H}^{3.1}\,{N}_{a}^{-0.8}$. Plain Language Summary: Precipitation plays an important role over the Southern Ocean (SO), such as transferring water from the atmosphere to the ocean, and affecting clouds and aerosols (tiny airborne particles). This study aims to characterize SO precipitation properties using aircraft data that can count the number and size of cloud and precipitation droplets, as well as lidar and radar that measure light and microwaves respectively reflected by droplets. Using information from lidar, we can distinguish the precipitation phase, and we find that ice precipitation is more frequent when the amount of reflected energy measured by the radar (radar reflectivity) is larger than a certain threshold. We derived relationships between rain rate and radar reflectivity. We also find the precipitation properties inferred from radar and lidar data compare well with direct measurements from the aircraft, and the precipitation tends to be very light. We study how precipitation properties vary vertically, and find that as one gets closer to the surface, there is a decrease in precipitation droplet number and water, while there is an increase in the average size of droplets. We also find that rain rate depends on how thick the clouds are and the number of aerosols, consistent with theoretical expectations. Key Points: Liquid‐phase precipitation retrievals show good agreement with in situ observations and feature the prevalence of light rainReflectivity to rain rate relationships are developed, showing vertical dependence and sensitivity to the intermediate‐sized dropsThe below‐cloud precipitation phase with radar reflectivity >0 dBZ is mostly ice, while radar reflectivity <−10 dBZ is mostly liquid [ABSTRACT FROM AUTHOR]

This study characterizes the variability in different parameters using high-frequency ground-based instruments, i.e., ceilometer and Micro Rain Radar (MRR), on a diurnal scale installed at the Indian Institute of Technology Bhubaneswar, Odisha, India. The study evaluates cloud base height (CBH) and boundary layer height (BLH) to understand their role in influencing convection from liquid water content (LWC), rain rate, radar reflectivity, and fall velocity over a tropical location for different seasons on a diurnal scale. The data retrieved from these surface-based instruments are segregated into four different seasons, i.e., pre-monsoon, monsoon, post-monsoon, and winter, for 2019 and 2020. It is noted that the atmospheric processes influencing convection and associated rainfall over the study location differ for different seasons. The frequency distribution of different types of clouds depending on their vertical levels, i.e., low-level clouds (LLC), mid-level clouds (MLC), and high-level clouds (HLC), during different seasons revealed a high occurrence of low- to mid-level clouds in pre-monsoon and post-monsoon seasons, mid-level clouds in the monsoon season, and low-level clouds in the winter season. The results also illustrate that the rainfall during different seasons largely depends on the types of clouds, i.e., LLC, MLC, and HLC, as detected from the CBH layers, which contribute to convection and rainfall over the study location. It is also revealed that the boundary layer processes in convection and rainfall influence the evolution of BLH during different seasons. Further, the study compares model skills in verifying boundary layer height and rainfall against surface-based observations. Besides characterizing the diurnal variability in these parameters on a daily scale, the study also elucidates the relationship between the cloud types and BLH. The results indicate that LLC occurrences were positively related to BLH during the pre-monsoon and monsoon seasons in 2019 and 2020. In contrast, a negative correlation is observed for cloud types MLC and HLC with BLH for the rest of the seasons of 2019 and 2020. Also, during post-monsoon and monsoon, distinct signatures of deep convection are noted over the study region, suggesting the influence of the boundary layer on MLC and HLC. The results from radar reflectivity and fall velocity during the monsoon and post-monsoon season support the influence of MLC and HLC on deep convection over the region. The diurnal variation in the observed parameters on a seasonal scale will help in understanding the role of various atmospheric parameters and processes in convection and associated rainfall over a tropical location and can provide necessary verification skills for weather and climate regional models against observations. [ABSTRACT FROM AUTHOR]

The current study investigates the relationship among Aerosol Optical Depth (AOD), rain rate in aerosol types (fine-mode and coarse-mode), and meteorological conditions (such as relative humidity and vertical velocity) during Indian Summer Monsoon (ISM) over regions of the Gangetic plain (GP) and the Modified Core Monsoon Region (MCMR) of India. The Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products, including AOD and Angstrom Exponent (AE), the observed rainfall gridded data of India Meteorological Department (IMD) and reanalyzed data of relative humidity (RH), vertical velocity (VV) and wind speed and direction as meteorological variables from European Center for Medium Range Weather Forecasting (ECMWF) Reanalysis v5 (ERA5) are used for the period of 2003–2021. It is noticed that regions of GP and MCMR experienced significant rainfall suppression with increasing aerosol loading in moderately polluted condition and beyond moderately polluted condition, the different rain rate responses to aerosol loading is observed. Different aerosol types and meteorological conditions may have different influences on the AOD-rain rate relationship. It is found that an increase in AOD may suppress or enhance the rain rate in a region like GP where high RH condition prevails, as well as the presence of fine-mode aerosol can enhance the rain rate in a highly polluted condition (AOD ≥ 0.4). An increase in AOD may enhance the rain rate in conditions of high and low RH over the regions. In high and low updraft conditions, an increase in AOD suppresses the rain rate. Additionally, high (low) RH and high (low) updraft promote high (low) rain rate over the regions. [ABSTRACT FROM AUTHOR]

The tropospheric delay acquired by the Global Navigation Position System (GPS) Precise Point Positioning (PPP) is continuous and steady, less affected by rainfall. The Water Vapor Radiometer (WVR) can provide real‐time meteorological parameters but is more sensitive to high‐frequency information in troposphere. To explore the use of WVR‐retrieved tropospheric delay and assist other geodetic techniques for atmospheric correction, the tropospheric delay from WVR and co‐located GPS at Shanghai, Beijing, Kunming, and Urumqi stations in China are compared. For the inconsistent values of WVR‐PPP zenith wet delay, the variations of the tropospheric delay from WVR and GPS before and after the rainfall were statistically analyzed. The results suggest that, for the rain rate ranging from 0.1 to 50 mm/hr, the impact of rainfall on WVR could last from 10 min before to 30 min after the rainfall. With filtering WVR data based on meteorological parameters and rain rate, the zenith wet delay between WVR and PPP at Shanghai shows good consistency, the root mean square (RMS) is 6.11 mm, correlation is 0.997, and the RMS in the other three stations ranges from 16.35 to 25.16 mm (correlation ranges in 0.794–0.951). The analysis indicates that the tropospheric delay of WVR is reliable to be applied to space geodetic techniques correction in real‐time with filtering to reduce the effect of rainfall, water vapor, and liquid water variability. Key Points: Comparison of zenith wet delay(ZWD) from water vapor radiometer, co‐located GPS station observations in high temporal resolutionQuantitative analysis of the magnitude and duration of rainfall effects on the zenith wet delay from water vapor radiometer and GPSSuch data analysis and processing might be valuable for assimilating multi‐source data on tropospheric wet delay [ABSTRACT FROM AUTHOR]

Rain fade causes signal attenuation which can relatively results in signal quality performance degradation, increased pathloss and coverage area reduction in satellite communication networks, most especially in the tropics and at higher operational frequencies above 10GHz. Analysis of rain attenuation provides useful insight for satellite communication engineers for efficient network planning and design within the region of study. Hence this paper presents threeyear analysis of signal-induced attenuation in the South-South States of Nigeria for the cities of Port-Harcourt, Uyo, Calabar and Eket, whose terrain characteristics could be generalized to represent urban, sub-urban and rural terrains in Nigeria. The International Telecommunications Union Radio-wave propagation (ITU-R P618-13) model was used to estimate the long-term rain attenuation at 10GHz, 20GHz and 30GHz for satellite communication applications. Results obtained at 10GHz, 20GHz and 30GHz operational frequencies show that at high frequency, rain fade can cause signal attenuation levels in the south-south region of Nigeria. In all, Calabar recorded the highest rain rate and corresponding highest attenuation level of 96.13dB at 30GHz compared to 50.29dB at 20GHz for the period under review. [ABSTRACT FROM AUTHOR]

The IMERG data product is an optimal combination of precipitation estimates from the Global Precipitation Mission (GPM), making use of a variety of data types, primarily data from various spaceborne passive instruments. Previous versions of the IMERG product have been extensively validated by comparisons with gauge data and ground-based radars over land. However, IMERG rain rates, especially sub-daily, over open ocean are less validated due to the scarcity of comparison data, particularly with the relatively new Version 07. To address this issue, we consider IMERG V07 30-min data acquired in tropical cyclones over open ocean. We perform two tasks. The first is a straightforward comparison between IMERG precipitation rates and those retrieved from the GPM Dual-frequency Precipitation Radar (DPR). From this, we find that IMERG and DPR are close at low rain rates, while, at high rain rates, IMERG tends to be lower than DPR. The second task is the assessment of IMERG’s ability to represent or detect structures commonly seen in tropical cyclones, including the annular structure and concentric eyewalls. For this, we operate on IMERG data with many machine learning algorithms and are able to achieve a 96% classification accuracy, indicating that IMERG does indeed contain TC structural information.

Heavy rain is associated with strong winds and extreme waves in a tropical cyclone (TC). In this letter, a practical algorithm for rain rate retrieval in TCs is proposed through 24 dual-polarized [vertical-vertical (VV) and vertical-horizontal (VH)] Sentinel-1 (S-1) synthetic aperture radar (SAR) images acquired in interferometric-wide (IW) swath mode, in which 13 images are collocated with the observations from stepped-frequency microwave radiometers (SFMRs). TC winds are directly obtained from VH-polarized images utilizing the geophysical model function (GMF) S-1 IW mode wind speed retrieval model after noise removal (S1IW.NR). The normalized radar cross section (NRCS) at VV-polarization channel is simulated using GMF CMOD5N and VH-polarized SAR wind. It is found that the difference between the simulated NRCSs and measurements from SAR is linearly related to the rain rate and oscillates with the incidence angle. Following this finding, an empirical algorithm for SAR rain rate retrieval is developed, denoted as CRAIN2_S1, which considers the influence of the radius of the maximum wind speed. The proposed algorithm is applied to 11 images in the dataset, and the validation of the rain rate (up to 35 mm/hr) against the products from global precipitation measurements (GPMs) has a root mean square error (RMSE) of 1.74 mm/hr, a correlation coefficient of 0.92 and a scatter index (SI) of 0.29. Collectively, it is concluded that the algorithm CRAIN2_S1 can be practically applied for dual-polarized SAR rain rate retrieval without any external information. [ABSTRACT FROM AUTHOR]

The propagation impairments by rain strongly affect the earth-to-satellite links operating at frequencies higher than 18 GHz mainly due to the severe performance degradation of satellite communication system. The time diversity technique with appropriate time delay between successive transmissions has been found effective in mitigating the rain fade. However, time diversity analysis demands measured rain attenuation data, where the latter is unavailable at most of the places to be able to design future high frequency links. The time diversity gain prediction model has been found to be robust for time diversity improvement. Here, we propose a new model for the rain rate with and without the time delay considering the three variables of rain rate, time delay and frequency. The rain rate and time delay functions were first used to derive the constants by the regression from the rain rate and rain rate gain. The constant for the frequency function was then extracted from the cumulative distribution function of the attenuation predicted by the analytically obtained ITU-R and gain equations. The proposed model was validated using one-year rain rate and attenuation data measured at two different locations in Malaysia demonstrating a 7% prediction inaccuracy when compared to the existing models, therefore, it can be reliably used for future earth-to-satellite link designs by using measured rain rate at any higher frequencies.

The purpose of this study was to develop a method for retrieving the rain rate from C-band (∼5.3 GHz) synthetic aperture radar (SAR) images during tropical cyclones (TCs). Seven dual-polarized (vertical–vertical [VV] and vertical–horizontal [VH]) Sentinel-1 (S-1) SAR images were acquired in the interferometric-wide (IW) swath mode during the Satellite Hurricane Observation Campaign. These images were collocated with rain rates measured by the Stepped-Frequency Microwave Radiometers onboard National Oceanic and Atmospheric Administration aircraft. Wind speeds were retrieved from the VH-polarized SAR images using the geophysical model function (GMF) S1IW.NR. We determined the difference between the measured normalized radar cross section (NRCS) based on VV-polarized SAR and the predicted NRCS derived using the GMF CMOD5.N forced with wind speeds retrieved from VH-polarized SAR images. Rain cells were identified as regions in the images where the NRCS difference was greater than 0.5 dB or smaller than −0.5 dB. We found that the difference in the NRCS decreased and the VH-polarized wind speed increased with increasing rain rate. Based on these findings, we developed an empirical function for S-1 SAR rain retrieval in a TC, naming it CRAIN_S1. The validation of the CRAIN_S1 results with Tropical Rainfall Measuring Mission data resulted in a root mean square error of 0.58 mm/h and a correlation of 0.89. This study provides an alternate method for rain monitoring utilizing SAR data with a fine spatial resolution.

Raindrops are an integral part of nature's hydrological cycle. Information on their sizes in different seasons and climatic conditions is required in many practical applications. We report seasonal average properties of rainfall examined through raindrop sizes and rain rates measured with optical disdrometers in India. Disdrometers were operated at three sites having coastal, orographic and continental climates. Analysis has been carried out by clubbing data of each station into two groups, namely, all available and summer monsoon season-only data. The study presents contributions of different raindrop sizes and rain rates to the total rainfall. There are between 2.4 and 2.9 million raindrops (with size > 0.25 mm) in one litre of rainwater, with the orographic site having the maximum number. A sum of two exponential functions describes the size dependence of number of drops present in rainwater. Major contribution to the monsoon rainfall comes from drops having sizes in 1.5–2.5 mm range with a peak of around 2 mm. Average rain accumulation with rain rate (R) approximately varies as R–b (for R > 0); b depends on location and lies between 1.1 and 1.3, the former corresponding to the continental site while the latter to the orographic. Research highlights: There are between 2.4 and 2.9 million raindrops (with size > 0.25 mm) in one litre of rainwater. Major contribution to the monsoon rainfall comes from drops having sizes in 1.5–2.5 mm range with a peak around 2 mm. On the other hand, all values of rain rate (R) are important to rain accumulation; low rain rate contributes by its sheer number (i.e., their total long duration) while large rain rate by its magnitude. Average rain accumulation varies as R–b, where b lies between 1.1 and 1.3 depending on location. [ABSTRACT FROM AUTHOR]

Rain attenuation is a major source of impairment to signal degradation at millimetre wave bands above 10 GHz. This research work determines the extent of signal degradation due to rainfall on terrestrial radio links within Minna and Lapai. The meteorological rainfall data collected from the Automatic Weather Stations installed at the Federal University of Technology, Minna, and at Ibrahim Badamasi Babangida University, Lapai, for a period of 3 years (2011-2013) were used to computate the rainfall attenuation on Microsoft Excel spreadsheets. The Lavergnat-Gole (LG) model was used for the conversion of cumulative distributions of rainfall of 5-min to 1-min integration time in Minna and Lapai respectively. The LG model was used to estimate the rain attenuation in the two stations at a frequency range of 10-18 GHz. The relationship between rain rate and specific attenuation was studied using three years rainfall data. It was observed that a power-law relationship exists between rainfall rates of different integration times. The results for the rain rate exceeded for 0.01% of time, show that the horizontal polarisation experiences more degradation than the vertical polarisation. The results also show that specific and total attenuations increase with increasing operational frequency and are polarisation-dependent. These results would be useful for planning terrestrial radio networks within the study area.

To understand the microphysical characteristics of rainfall in four different climatological regions (called BOS, BUS, CPO, and JIN) in South Korea, DSDs and their variables, including the mass-weighted mean diameter (Dm) and normalized number concentration (logNw), were examined. To examine the characteristics of DSDs at four sites with different climatology and topography, data measured from Parsivel disdrometer and wind direction from Automatic Weather System (AWS) during rainy seasons from June to August for three years (2018 to 2020) were analyzed. The DSDs variables were calculated using Gamma distribution model. In the coastal area, larger raindrops with a lower number concentration occurred, whereas smaller raindrops with a higher number concentration dominated in the middle land and mountain region. The mountain area of CPO and middle land area of JIN had a larger contribution to the rain rate than that of the coastal area of BOS and JIN in the range of the smallest diameter. The contribution of the drop size to the total number concentration at the CPO and JIN sites was larger (smaller) than that at BOS and BUS in the smallest (larger) diameter. The average shape and slope parameter of gamma model were higher values at the mountain area than at other sites for both rain types, Z-R relation and polarimetric variables were also shown different values at the four studied sites. The intercept coefficient of Z-R relation showed higher values in the mountain area and middle land area than the coastal area. The slope values of Z-R relation were the smallest in the mountain area. The polarimetric variables of ZH and ZDR were shown highest (lowest) value at the coastal region of BOS (mountain area of CPO) site for both rain types. The Dm-rose, which shows the Dm distributions with the wind direction, was used in this study. In the coastal area (mountain and middle land area), the dominant wind was east–southeast (east) direction. The ratio of the smaller diameter to the middle size at BOS was much smaller than that at CPO. In the analysis of the hourly distribution of the Dm and logNw, there were two and four peaks of Dm at BUS and BOS, respectively. There was one peak of the Dm at the CPO and JIN sites. The time variation of the Dm was much higher than that of the logNw. [ABSTRACT FROM AUTHOR]

Abstract Rain attenuation is considerably noticed in a frequency spectrum above 7-GHz for tropical equatorial regions and in a frequency spectrum higher than 10-GHz for temperate climates. The attenuation prediction method provided by the International Telecommunication Union-Recommendation (ITU-R), through Recommendation P.530-16 and P.618-13 utilize data collected from temperate regions. Since the average raindrop size is bigger and the rainfall rate is high in magnitude in tropical regions than that of non-tropical areas, this prediction model is not suitable for the measured rain data. Unfortunately, a rain fade mitigation technique based on local rain data has not been adequately studied in tropical regions. This paper presents an enhanced adaptive code modulation (ACM) for rainfall fade mitigation in Ethiopia. In this research work, locally collected one-minute rain rate data is used to determine the rain attenuation. Then based on this result, the neuro-fuzzy inference system is employed to enhance the mitigation technique. Furthermore, a comparison of the performance of this proposed scheme is with the non-adaptive technique, and fuzzy-based adaptive modulation and coding technique is carried out. MATLAB simulation result showed that lower-order quadrature amplitude modulation (QAM) scheme with a lower convolutional coding rate is better in maintaining link availability in bad weather conditions. However, spectral efficiency is improved by utilizing a larger constellation size of quadrature amplitude modulation (QAM) scheme with a higher convolutional coding rate when the channel is not affected by rain.

Tropical cyclones (TCs) can undergo offshore rapid intensification (RI) shortly before making landfall over the South China Sea (SCS). In this study, the inner rainbands distribution of both RI and non-RI landfall TCs (LTCs) in the SCS during 2015–2020 is examined based on a multi-source merged precipitation dataset. It is found that those RI LTCs exhibit a relatively higher averaged rain rate in the inner core region than that of non-RI LTCs. Both offshore RI cases and non-RI LTCs appear to have an increasing tendency of averaged rain rate after landfall, with the rain rate peak of the RI cases a few hours earlier than that of non-RI cases. By defining an axisymmetric index, the inner rainband evolution of both offshore RI cases and non-RI ones are further discussed. For both categories, most of the axisymmetric rainfall is concentric around the center and over 70% axisymmetric rainfall dominates the inner core region within three times of radius of maximum wind speed (RMW). It is shown that there is an obvious inwards shrinkage of axisymmetric rainfall for both offshore RI and non-RI cases. Analysis of typical RI and non-RI LTCs (1713 Hato and 1714 Pakhar) also shows an increasing rain rate of the inner rainbands soon after landfall, with larger amplitude for RI example than non-RI case. The inner rainbands of 1713 Hato show that a clockwise propagation with maximum enhancement happened at the down-shear left-hand side a few hours after landfall.

Precipitation is a key component of the hydrological cycle, which is critical to understanding its formation and evolution. In this study, based on the observation data of the PWS100 located at the meteorological observation site at the terminal of Urumqi Glacier No. 1, eastern Tianshan Mountains, the statistical characteristics of the summer raindrop size distribution (DSD) were analyzed, and the DSD characteristics of five different rainfall rates(R) and two rainfall types (convective and stratiform) were investigated for the daytime and nighttime. The average raindrop spectral width was the largest in class III (1 < R < 5 mm h−1). The result showed that the raindrop concentration increased with the rainfall rate. The maximum raindrop concentration was at class IV (5 < R < 10 mm h−1), when the raindrop diameter was higher than 1.74 mm. The small and medium size raindrops played a dominant role in precipitation composition in the head watershed of the Urumqi River, contributing 98% of the total raindrop. The convective precipitation at the headwaters was divided into continental clusters. The stratiform/convective Dm-log10Nw was characterized by a large mass-weighted mean diameter Dm = 1.523/2.608, and a generalized intercept log10Nw = 2.841/3.469. N(D) of convective precipitation was significantly different between the daytime and nighttime, while that of stratiform precipitation was almost the same. The constraint relationship between R-Dm and R-log10Nw of these two precipitation types was deduced, the exponent of the R-log10Nw relationship of the two precipitation types was negative, and the Dm value of stratiform precipitation tended to be stable at a higher rainfall rate (1–2 mm). Finally, we deduced the power-law relationship between radar reflectivity (Z) and rain rate (R) [Z = A*Rb] for stratiform and convective precipitation at the headwaters. Z = 698.8R2.0 was for stratiform, and Z = 47.1R2.0 was for convective. These results, for the first time, offer insights into the microphysical nature of precipitation in the head watershed of the Urumqi River during the summer and provide essential information that could be useful for precipitation retrievals based on weather radar observations.

Future satellite companies will use higher Ka and V bands. Rain fade is the most important issue in establishing reliable communication between Earth and satellites outside the 10 GHz band. The problem is exacerbated in the tropics by significant rainfall throughout the year. One way to deal with rainfall attenuation is to use a time-diversity strategy. Real-time rainfall attenuation data is needed to analyze time variability. However, data from higher frequency bands such as Ka and V bands cannot be used. As a result, the Synthetic Storm Technique (SST) was proposed to convert the measured real time rainfall data into rainfall attenuation data and predict the time diversity gain. The measured rainfall data was converted to rainfall attenuation data using the traditional SST method. Time diversity gains were predicted using Converted rainfall attenuation and the Matriciani model, and the measurements were significantly overestimated. A new concept of realtime rainfall with and without time delay is proposed and used to predict time diversity gain using ITU-R P. 618-13 and the measured rainfall distribution with delay. Therefore, the proposed method recommends using the measured long-term precipitation data to predict the gain from time diversity at the desired frequency. [ABSTRACT FROM AUTHOR]

The impact of vertical downdraft on rain attenuation estimation from rain rate measurements has been studied. The rain rate (R) and specific attenuation (γ) are derived from rain drop size distributions (DSD) by considering the widely accepted Gunn–Kinzer (G-K) relationship between drop size and drop fall velocity that is valid for stagnant air. In the real atmosphere, drops are carried with the vertical wind draft, and the actual fall velocity of the raindrops deviates from the G–K formulation. The ITU-R estimated rain attenuation values, based on DSDs, which are mostly valid for temperate regions, can deviate from actual rain attenuation measurements in tropical regions, especially at higher rain rates when downdraft is prominent. The present study uses disdrometer measurements of DSD, optical rain gauge measurements of rain rates, and Ku-band rain attenuation data over an earth-space path at a tropical location Kolkata (22°34′ N, 88°29′ E) to show that vertical downdrafts impact the rain attenuation estimation from rain rate measurements. At the present location, an overall representative vertical downdraft of 2 m/s needs to be considered to match the experimental attenuation measurements with the estimated values using the modified γ–R relationship in the ITU-R model. [ABSTRACT FROM AUTHOR]

Accurate and near-real-time rain information at fine scales is critical for forecasting local weather and floods. Traditional classical infrared (IR) cloud-top brightness temperature data alone do not contain sufficient precipitation-related information, and the introduction of visible (VIS) observations limits their applications to daytime. Methods for the efficient and comprehensive utilization of multichannel IR observations for accurately retrieving all-day near-real-time rain rates with consistent high quality warrant further exploration. In this study, we propose an all-day near-real-time quantitative precipitation estimation framework based on multispectral analysis (MSA) from the Advanced Geosynchronous Radiation Imager (AGRI) onboard Chinese FY-4 series satellites; the proposed framework is called FY4QPE- MSA. Multiple IR bands are comprehensively and efficiently considered by adopting the principal component analysis technique to reduce the dimensionality to a few independent features while preserving most of the variations. The main conclusions include, but are not limited to, the following aspects: 1) the MSA from IR channels provides valuable information that facilitates the more accurate delineations of the precipitation occurrences; 2) FY4AQPE -MSA outperforms FY4AQPE- Offical [ $\sim 20$ % gain in the Pearson correlation coefficient (CC), $\sim 25$ % gain in the root mean square error (RMSE), and $\sim 15$ % gain in the critical success index (CSI)], FY4AQPE-Single ($\sim 10$ % gain in CC, $\sim 15$ % gain in RMSE, and $\sim 15$ % gain in CSI), and Precipitation Estimation from Remotely Sensed Information using artificial neural network-cloud classification system (PERSIANN-CCS) ($\sim 30$ % gain in CC, $\sim 20$ % gain in RMSE, and $\sim 25$ % gain in CSI); and 3) compared with the international IR-based baseline precipitation product, i.e., PERSIANN-CCS, FY4AQPE-MSA demonstrates no spatial gaps over the Tibetan Plateau. In addition, the results of this study suggest that the proposed general framework is promising and applicable for Chinese FY-4 series satellites in generating all-day near-real-time rain-rate information. [ABSTRACT FROM AUTHOR]

This study analyzes the raindrop size distribution (RSD) characteristics over New Delhi by dividing the year into three seasons: PreM (March–May), monsoon (June–September), and PostM (October–February). Data from a Joss-Waldvogel Disdrometer, installed at IITM New Delhi, Rajendra Nagar, was used for three years (2021–2023). The observed raindrop spectra were fitted with three-parameter Gamma functions to obtain the RSD. ERA-5 and satellite data were also employed to establish atmospheric and cloud properties for the three seasons. The RSD for the monsoon season shows the highest concentration of midsize (1–3 mm diameter) drops and the highest mean rain rate. PostM has the least concentration of midsize and large (diameter >3 mm) drops. General statistics of rain integral parameters reveal high variability in rain rate (R) and mass-weighted mean diameter (D m) values during the monsoon season. The mu-lambda scatter plots show considerable differences among the three seasons, indicating slightly distinct rainfall mechanisms in the three seasons. Z - R relations of the form Z = a R b were derived, with the highest coefficient (a) values observed for the PreM precipitation. The exponent (b) is found to be greater than unity in all three seasons. Rainfall was stratified based on rain rate. RSD gets broader with increasing R. Large drops are not found appreciably in the spectrum for R < 20 mm/h. A notable disparity between convective and stratiform RSD is evident. The values of rain integral parameters show considerable differences between the convective and stratiform regimes. A higher fraction of large drops is found for the stratiform rainfall in the PreM season compared to the other two seasons. CAPE, water vapor, surface temperature, and surface winds were higher during PreM and monsoon months compared to PostM. The distribution of differential temperature (δT) indicates that clouds with significant depth are found in PreM and monsoon seasons but are often lacking during PostM. • First attempt to understand the surface rainfall microphysics over Delhi. • Z-R relations derived for every season over Delhi for both stratiform and convective precipitation type. • Results suggest formation of bright bands during stratiform rainfall in PreM season. • Use of reanalysis and satellite data to understand the mean background meteorological conditions during the three seasons. [ABSTRACT FROM AUTHOR]

Rain attenuation is considerably noticed in a frequency spectrum above 7-GHz for tropical equatorial regions and in a frequency spectrum higher than 10-GHz for temperate climates. The attenuation prediction method provided by the International Telecommunication Union-Recommendation (ITU-R), through Recommendation P.530-16 and P.618-13 utilize data collected from temperate regions. Since the average raindrop size is bigger and the rainfall rate is high in magnitude in tropical regions than that of non-tropical areas, this prediction model is not suitable for the measured rain data. Unfortunately, a rain fade mitigation technique based on local rain data has not been adequately studied in tropical regions. This paper presents an enhanced adaptive code modulation (ACM) for rainfall fade mitigation in Ethiopia. In this research work, locally collected one-minute rain rate data is used to determine the rain attenuation. Then based on this result, the neuro-fuzzy inference system is employed to enhance the mitigation technique. Furthermore, a comparison of the performance of this proposed scheme is with the non-adaptive technique, and fuzzy-based adaptive modulation and coding technique is carried out. MATLAB simulation result showed that lower-order quadrature amplitude modulation (QAM) scheme with a lower convolutional coding rate is better in maintaining link availability in bad weather conditions. However, spectral efficiency is improved by utilizing a larger constellation size of quadrature amplitude modulation (QAM) scheme with a higher convolutional coding rate when the channel is not affected by rain. [ABSTRACT FROM AUTHOR]

The radar monitor of aircraft wake vortex is of great significance to air traffic control. Comparing with the case in clear air, the radar signal of wake vortices in rainy conditions is more easily captured due to the higher levels of signal. To able to analyze radar echo characteristics of evolving wake vortices, the numerical simulation of the evolution of the wake vortices in various rain rates has been performed based on the Euler-Euler frame. The result shows that the rainfall can accelerate the decay of wake vortices. A radar simulator has been represented to process the radar echo signal of raindrops around the wake vortex. The Doppler spectrum of echo signals in radar resolution volumes has been analyzed and the straight vortex and the vortex ring phases show different characteristics of spectrum width. The Doppler width information based on this result of interaction between the wake vortex and rain can be used for assessing the decay phase of wake vortices and monitoring potential hazard for wake vortex encounters.

Rain attenuation is the main practical problem that confronts wireless signals specifically when it uses millimeter-waves for fifth-generation (5G) communication systems. In addition, due to that the urban environments are characterized by many high buildings act as diffraction objects can block the signal path and produce non-line of sight (NLOS) situations. These diffraction materials can cause further considerable losses that disturb the received power at the 5G receiver. This paper proposes a new model can investigate the influence of both precipitation and diffraction phenomena on wireless point to point (PPT) communication systems. This new research work utilizes measured rainfall data and actual scenarios in an urban environment to simulate the wireless PPT system and examine the influence of rainfall and knife-edge diffraction (KED) on the performance of the PPT system and signal strength at the receiver. Several durations of exceedances of rain rates and various operation scenarios have been employed to study and analyze the status of 5G wireless system links. The results indicated that there is an exchange of the effect of rain and KED diffraction in the lower millimeter-waves compared to the higher millimeter-waves. This study declares that at higher frequency bands the rain attenuation is observed to be greater, the diffraction loss is higher, and the path loss is also larger compared to the effect of these three factors seen at lower frequency bands. Furthermore, specific carrier frequencies, as in the case of 60 GHz, undergo extra huge atmospheric absorption loss which can diminish the communication coverage of the PPT system link.

To understand the microphysical characteristics of rainfall in four different climatological regions (called BOS, BUS, CPO, and JIN) in South Korea, DSDs and their variables, including the mass-weighted mean diameter (Dm) and normalized number concentration (logNw), were examined. To examine the characteristics of DSDs at four sites with different climatology and topography, data measured from Parsivel disdrometer and wind direction from Automatic Weather System (AWS) during rainy seasons from June to August for three years (2018 to 2020) were analyzed. The DSDs variables were calculated using Gamma distribution model. In the coastal area, larger raindrops with a lower number concentration occurred, whereas smaller raindrops with a higher number concentration dominated in the middle land and mountain region. The mountain area of CPO and middle land area of JIN had a larger contribution to the rain rate than that of the coastal area of BOS and JIN in the range of the smallest diameter. The contribution of the drop size to the total number concentration at the CPO and JIN sites was larger (smaller) than that at BOS and BUS in the smallest (larger) diameter. The average shape and slope parameter of gamma model were higher values at the mountain area than at other sites for both rain types, Z-R relation and polarimetric variables were also shown different values at the four studied sites. The intercept coefficient of Z-R relation showed higher values in the mountain area and middle land area than the coastal area. The slope values of Z-R relation were the smallest in the mountain area. The polarimetric variables of ZH and ZDR were shown highest (lowest) value at the coastal region of BOS (mountain area of CPO) site for both rain types. The Dm-rose, which shows the Dm distributions with the wind direction, was used in this study. In the coastal area (mountain and middle land area), the dominant wind was east–southeast (east) direction. The ratio of the smaller diameter to the middle size at BOS was much smaller than that at CPO. In the analysis of the hourly distribution of the Dm and logNw, there were two and four peaks of Dm at BUS and BOS, respectively. There was one peak of the Dm at the CPO and JIN sites. The time variation of the Dm was much higher than that of the logNw.

• 1-min and 5-min integration time rain rates were measured. • Two rain rate models were used to predict 1-min rain rate. • The measured and predicted 1-min rain rates were compared. • Lavergnat-Gole model is the optimal rain rate prediction model. An important characteristic of rainfall levels at a particular place is the statistical distribution of rainfall rate. In this paper, 5-min integration time rainfall data for the Northcentral region of Nigeria was obtained from the Tropospheric Data Acquisition Network (TRODAN), Anyigba, Nigeria. Also, 1-min integration time rainfall was measured at Minna, Nigeria. In order to obtain the optimal rain rate model suitable for this region, two globally recognised rain rate models were critically evaluated and compared with the 1-min measurements. These are the ITU-R P.837-7 and Lavergnat-Gole (L-G) models. The results obtained showed that the ITU-R P.837-7 and L-G models respectively underestimated the measured rain rate by 7.3 mm/h and 9 mm/h at time percentage exceedance of 0.1%, while they underestimated the measured rain rate by 23.4 mm/h and 13 mm/h respectively at 0.01%. At 0.001%, the measured rain rate was overestimated by the ITU-R P.837-7 and L-G models by 27.4 mm/h and 3 mm/h respectively. Further performance evaluation of the predefined models was carried out using different error metrics such as sum of absolute error (SAE), mean absolute error (MAE), root mean square error (RMSE), standard deviation (STDEV) and Spearman's rank correlation. The results obtained adjudged the Lavergnat-Gole model as the best rain rate prediction model for this region. [ABSTRACT FROM AUTHOR]

The current study addresses the role of heat and moisture emitted from anthropogenic sources on the local weather with the aid of numerical weather prediction (NWP). The heat and moisture emitted by industries to the atmosphere are considered main sources in this study. In order to understand the effect of heat and moisture on local weather, the study is conducted to capture the impact of heat with no moisture change. The results are compared against a control run case without perturbation and also against the case where both heat and moisture are perturbed with temperature as a single parameter. The Angul district in Odisha that houses over 4000 industries is considered our study region. The numerical simulations are performed using the mesoscale Weather Research and Forecasting (WRF) model for two rain events, namely a light rain case and a heavy rain case, with different physics options available in the WRF model. The WRF simulated maximum rainfall rate using various microphysics schemes are compared with the Tropical rainfall measuring mission (TRMM) observations for validation purposes. Our study shows that the WDM6 double moment microphysics scheme is better in capturing rain events. The TRMM-validated WRF simulation is considered a reference state of the atmosphere against which comparisons for the perturbed case are made. The surface temperature is perturbed by increasing it by 10 K near the industrial site and exponentially decreasing it with height up to the atmospheric boundary layer. A numerical experiment represents heating without addition of moisture by recalculating the relative humidity (RH) corresponding to the perturbed temperature. The perturbed temperature affects sensible heat (SH) and latent heat (LH) parameters in the numerical experiment. From the results of the numerical investigation, it is found that the near-surface rainfall rate increases locally in a reasonable manner with the addition of sensible heat to the atmosphere. A comparison against the case where moisture is added shows that enhanced rainfall is more sensitive to sensible and latent heat than sensible heat alone.

Three years of reanalysis and ground‐based observations collected at the Eastern North Atlantic (ENA) observatory are analyzed to document the properties of rain and boundary layer clouds and their relationship with the large‐scale environment during general subsidence conditions and following cold front passages. Clouds in the wake of cold fronts exhibit on average a 10% higher propensity to precipitate and higher rain‐to‐cloud fraction than cloud found in general subsidence conditions. Similarities in the seasonal cycle of rain and of large‐scale properties suggest that the large‐scale conditions created by the cold front passage are responsible for the unique properties of the rain forming in its wake. The identification of monotonic relationships between rain‐to‐cloud fraction and rain rate with surface forcing and boundary layer stability parameters as well as between virga base height with stability and humidity measures further supports that large‐scale conditions impact precipitation variability. That being said, these relationships between the large‐scale and rain properties are less clear than those established between cloud and rain properties, suggesting that cloud macrophysics have a more direct impact on the properties of rain than the large‐scale environment. The applicability of previously documented relationships between cloud thickness and rain properties is tested and the relationships adjusted to accommodate the complex shallow clouds and melting precipitation observed to occur in the ENA region. Establishing these relationships opens up opportunities for parametrization development and suggests that a realistic representation of precipitation properties in models relies on the accurate representation of both clouds and the large‐scale environment. Key Points: During periods of large‐scale subsidence in the Eastern North Atlantic, rain properties are strongly related to cloud thickness even in ice‐topped cloudsLikely because of their relationship to cloud thickness, surface forcing and boundary layer stability impact rain fraction and rain ratePost‐cold frontal shallow clouds precipitate more frequently and have a higher rain‐to‐cloud fraction than clouds in general subsidence [ABSTRACT FROM AUTHOR]

A Ka-Band signal propagation study under tropical monsoon climate has been taken up jointly by ISRO/ONERA/CNES. The program has been aimed at finding the degree to which Ka-Band satellite signals get affected by rain. Dual polarized Ka Band beacon signals onboard GSAT-14 satellite, of frequencies 20.2 GHz and 30.5 GHz, have been used for the experiment. Data available by various instruments has been compared with ITU-R predicted values. Results for the years 2016 and 2017 at Umiam has shown underestimation of both Rainfall and Signal Attenuation by ITU-R predicted models. It has also been found that the Rainfall has been mostly concentrated in three months (June, July, August) and the maximum attenuation that Ka-Band signals have suffered during rain at Umiam has been around 30-40 dB. The actual Rainfall and Attenuation of both 20.2 GHz and 30.5 GHz signals have been compared with ITU-R predictions and has been found to be much above the predicted levels. A Study of the Z-R relationship for the rainfall and comparison with known relations has indicated that a new distribution is required for the region. [ABSTRACT FROM AUTHOR]

Forest canopies present irregular surfaces that alter both the quantity and spatiotemporal variability of precipitation inputs. The drop size distribution (DSD) of rainfall varies with rainfall event characteristics and is altered substantially by the forest stand properties. Yet, the influence of two major European tree species, European beech (Fagus sylvatica L.) and Norway spruce (Picea abies (L.) H. Karst), on throughfall DSD is largely unknown. In order to assess the impact of these two species with differing canopy structures on throughfall DSD, two optical disdrometers, one above and one below the canopy of each European beech and Norway spruce, measured DSD of both incident rainfall and throughfall over 2 months at a 10‐s resolution. Fractions of different throughfall categories were analysed for single‐precipitation events of different intensities. While penetrating the canopies, clear shifts in drop size and temporal distributions of incoming rainfall were observed. Beech and spruce, however, had different DSD, behaved differently in their effect on diameter volume percentiles as well as width of drop spectrum. The maximum drop sizes under beech were higher than under spruce. The mean ± standard deviation of the median volume drops size (D50) over all rain events was 2.7 ± 0.28 mm for beech and 0.80 ± 0.04 mm for spruce, respectively. In general, there was a high‐DSD variability within events indicating varying amounts of the different throughfall fractions. These findings help to better understand the effects of different tree species on rainfall partitioning processes and small‐scale variations in subcanopy rainfall inputs, thereby demonstrating the need for further research in high‐resolution spatial and temporal properties of rainfall and throughfall. [ABSTRACT FROM AUTHOR]