Rainfall Rate Research Articles

Evaluation of the probability of overflow from the Abadia de Goiás repository by the Fokker-Planck equation using the Trotter’s formula

A model was constructed with the objective of developing the Fokker-Planck equation for the calculation of the reliability attributes required for risk-informed decision-making involved in the analysis of water infiltration inside the repository located in the Abadia de Goiás municipality, in the metropolitan region of the city of Goiânia. The solution of the Fokker-Planck equation was analytically obtained by the Trotter’s method for a near surface repository. This solution provides the probability density and the probability functions for the height of the liquid (water + radionuclides) column, generated by the infiltrated water in the concrete crypt of the repository. The modeling was unidimensional, and the calculations were performed for the geometric center of the repository crypt, which is the place of greater sensitivity of occurrence of accidental scenarios. The concept of the present model can be extended to other places in the crypt without loss of generality. The developed model is appropriate to analyze the repository overflow, a kind of event that occurs when the height of the liquid column inside the repository reaches the value of the inner height of the concrete crypt of the facility. This accident scenario produces the greatest release of radioactive material to the region outside the repository and, consequently, it is responsible for the main radiological impact for both members of the public and the environment. Calculations performed for the Abadia de Goiás repository indicated that the overflow probability for this facility is strongly dependent on the rainfall rate and also on the institutional time period, varying from about 3% with no rainfall penetration up 99% with the maximum rainfall rate for an institutional time period control of 300 yr. Such results can help making decisions on the problem of risk scenarios related to the disposal of radioactive waste.

Enhanced Technique for Prediction of Z-R Relationship in Tropical Region

Over the years, research has been directed to investigate radar as potential tools for estimating rain. The radar reflectivity is measured by comparing the location of the rain gauge and the associated vertical path at certain altitude. The latitude and longitude of the rain gauge is identified to pinpoint the exact associated location by using Rainbow®5 meteorological software. In this work, radar reflectivity was estimated by using S-band Terminal Doppler Weather Radar (TWDR) data at Malaysian KLIA radar station. The rain gauge is owned by Malaysian Department of Irrigation and Drainage (DID) at several locations within the vicinity of the radar. A technique to estimate the Z-R relationship by using radar reflectivity information and rainfall rate from rain gauge values is demonstrated in this article. Comparisons between radar reflectivity and actual rain gauge measurement is presented. Preliminary findings using available Z-R relation shows similar values with the actual measurement and suitable to be used in tropical climate country such as Malaysia.

The Impact of ENSO on the Precipitation in Iraq Regions

Abstract Precipitation is considered one of the important weather variables in determining the climate of any region in the world, and perhaps the precipitation in Iraq is witnessing an incomprehensible seasonal fluctuation. The work tries to identify the reasons for this fluctuation, from one season to another. The monthly average precipitation data in Iraq was obtained by Global Precipitation Climatology Project GPCP. Also, data for sea surface temperature anomalies (SST) for the four El Nino regions, as well as relative humidity and zonal wind speed were obtained from the National Centres for Environmental Prediction NCEP and National Centre for Atmospheric Research NCAR. The study period extended from 1980 to 2022, where the correlation of monthly precipitation average in Iraq with El Nino and La Niña events was tested, and it was found that there was a positive proportional effect of the El Nino event on the increase in rainfall rates in Iraq, the correlation coefficient R about 0.8 in North and Northern-East of Iraq. To explain this, the correlation between El Niño events, relative humidity, and zonal wind speed was tested. It was found that there is a proportional effect of El Nino on the relative humidity and an inverse effect on the zonal wind speed. Central and southern Iraq is less affected by El Niño and La Niña events, as the correlation coefficient of monthly precipitation average with El Niño phenomenon is approximately 0.5 to 0.6.

In-Excess Attenuation Detection Using Satellite Link Channel Measurements at Ka- and Q-Bands With Deep-Learning Architectures

In this paper a robust process to detect the existence of in excess attenuation values in the next future time-steps based on measured data from previous time-steps is provided for satellite channel measurements campaign at frequencies above 10 GHz. The straightforward process of anomaly detection is applied, where ’normal’ data, i.e. attenuation values lower than a threshold, are used to learn their predictive error probability. Afterwards a sequence is detected as ’normal’ or ’abnormal’ based on the Mahalanobis distance of its errors from the learnt distribution. Deep learning architectures, such as encoder-decoder and traditional paradigms are investigated and tested for different regions (Greece and U.K.) and frequency bands (Q and Ka downlinks). The method’s performance is very promising and the rainfall rate information seems valuable and adequate for attenuation’s detection. Finally, under a ’plug-and-play’ logic, the trained detectors in Greece exhibit high performance also in U.K. data showing the robustness of the proposed detection ability.

Propagation Methods and Mulching Modulate the Quantum Yield, Ionic Relations, and Production Components of Sour Passion Fruit under Salt Stress

In semiarid regions of Brazil, water and/or soil salinity is one of the limiting factors for sour passion fruit production. Low rainfall rates combined with edaphic conditions (high concentrations of soluble salts) intensify deleterious effects on plants. Thus, strategies that minimize the effects of salt stress, e.g., grafting with tolerant species and soil mulching, are extremely important to ensure the expansion of irrigated fruit farming in this region. From this perspective, this study aimed to evaluate the effect of grafting and mulching on the quantum yield, ionic relations, and fruit production of sour passion fruit irrigated with moderately saline water. The experiment was conducted under field conditions in split plots, in a 2 × (2 × 2) factorial arrangement to evaluate the combination of low and moderate salinity water (main plot) with the propagation method (seeds and grafting on P. cincinnata) and without and with plastic mulching (subplots), with four replications and three plants per plot. The ionic relations in passion fruit leaves were increased with the use of rootstocks and plastic mulching under irrigation with moderately saline water. The use of mulching increased the yield of photosystem II in sour passion fruit. The passion fruit plants propagated by seeds had 187.52% more fruits than those grafted onto P. cincinnata. The use of rootstocks with P. cincinnata in sour passion fruit restricted the uptake of Na and Cl but reduced fruit production.

Regional discrepancies in the microphysical attributes of summer season rainfall over Taiwan using GPM DPR

Taiwan, an island located in the northwest Pacific region, is influenced by heavy rainfall events during warm seasons, particularly from June to August. Interaction of precipitating clouds with the complex topography results in inhomogeneous and intense rainfall over Taiwan. Hence, the present study investigates the regional discrepancies in the microphysical characteristics of summer season rainfall over (north, south, east, and central) Taiwan using 9 years (2014–2022) of GPM DPR measurements. The results showed clear distinctions in the precipitation and raindrop size distributions over the north, south, east, and central Taiwan. The contoured frequency by altitude diagrams (CFADs) of radar reflectivity, rainfall rate, drop diameter, and concentration clearly infer the dominance of large-size super cooled liquid and ice particles above the melting layer and rain particles below the melting layers in the south and central Taiwan. Central (north) Taiwan is dominated by large-size (small) drops among four regions. Higher concentrations of large drops over central Taiwan (principally from convective precipitation) and south Taiwan (primarily from stratiform precipitation) is attributed to higher rainfall amounts over these two regions than the north and east Taiwan. Furthermore, irrespective of precipitation type and geographic region, summer monsoon rainfall over Taiwan is dominated by coalescence and breakup processes. The microphysical characteristics of summer season rainfall addressed in this study could assist in refining the cloud modeling simulations over complex topography in Taiwan.

Chemical Composition of Wet Atmospheric Deposition in a Natural Urban Reserve, Conservation of Green Urban Areas: a Mexico City Case Study

Green areas are essential for life in cities and for the conservation of ecosystem services in the case of megacities such as Mexico City. Green areas mitigate air pollution, reduce the temperature, and promote infiltration to feed the aquifers that, in the case of Mexico City, supply 68% of the water. Additionally, food production and recreational usage are important for the population. In the years 2017 and 2018, the chemical composition of wet deposition in the southern part of Mexico City was analyzed, daily and weekly. The study area is located in the greenest part of Mexico City, an important site for water recharge and carbon sequestration. Mexico City, like other megacities of high- and low-income countries, faces serious problems of air pollution. The purpose of this study was to measure the amount of total nitrogen and sulfur that is available in a natural reserve located inside the National Autonomous University of Mexico, and conductivity, pH, rain volume, and anions and cations were analyzed as well. Eighteen months of data were analyzed in order to understand the atmospheric deposition in and anthropogenic influence on an urban green natural area from the southern part of the city. Although both stations are less than 2 km apart, there are significant differences in their chemical composition; however, no differences were found for precipitation and pH, indicating that each station provides a local contribution, depending on local events and sources. Samples included rain events match for both sampling sites, with 67% of the samples in the same rain event match. Nonetheless, when only volume is compared for each year, both tests showed no significant difference (pv = 0.520). Throughout the year, various rainfall rates occur at the CU-CCA and REPSA stations, and the rainy season presents during the May–October period; the median value registered for both monitoring stations was 780 mL, and maximal rainfall was 4780 mL presenting at the CU-CCA station.

Biothermal Heating on Human Skin by Millimeter and Sub-Terahertz Waves in Outdoor Environment—A Theoretical Study

The frequency band in the millimeter-wave (MMW) and sub-terahertz (sub-THz) range has shown great potential in mobile communication technology due to the advantages of ultra-large bandwidth and ultra-high data rates. Based on the increasing research activities on MMW/sub-THz waves, biological safety at relevant frequencies must be explored, especially when high-power illumination occurs. Here, its non-ionizing nature plays a vital role, which makes it safe for humans at low illumination powers. However, under high power, the biothermal heating on the skin surface is still a main concern, and lots of research has been conducted in a laboratory. In this article, we analyze the thermal heating effect of human skin in outdoor environments, where atmospheric conditions can significantly impact the propagation of MMW/sub-THz waves. Our analysis is based on rat skin, which has a similar structure to human skin. A theoretical model combining Pennes’ bioheat transfer equation (BHTE), the ITU model, and the Mie scattering theory is developed. Good agreement between calculation results and measured data confirms the efficiency of this model. The influence of rainfall rate, humidity, operating frequency, illumination time, power density, and propagation distance is presented and discussed.

Simulation of a Dust‐And‐Rain Event Across the Red Sea Using WRF‐Chem

AbstractWe present simulations of a series of dust‐and‐rain events in July/August 2020 that caused significant loss of life and property over northeast Africa and the Red Sea coast using convection‐permitting Weather Research and Forecasting‐Chem simulations at 1.5 km horizontal grid spacing coupled with prognostic dust and aerosol scheme together with a double‐moment cloud microphysical scheme. The model generally captures the optical properties and vertical profiles of dust but has difficulty reproducing the seasonal dust plumes that originate over northeast Africa and reach the western Arabian Peninsula through the Tokar gap. Overlapping of synoptic events with local, diurnal‐scale, convective features caused continuous rainfall over the study domain in July/August 2020. The model well simulates the synoptically‐driven clouds over the ocean (∼4–8 km) and daytime deep convective clouds over the land but cannot reproduce cumulus clouds over the ocean advected from land, which leads to some biases in simulating peak rainfall rates. Although our simulations do not explicitly consider aerosol particles as ice nuclei, the model reproduces the cirrus clouds found at ∼10–15 km height during the study period. Simulations with a planetary boundary layer (PBL) scheme better represented the diurnal profile of surface temperature and winds, as well as the rainfall distribution, than without using a PBL scheme. Dust generally enhanced rainfall during the synoptic rain event through indirect effects but suppressed rainfall during sea‐breeze‐induced convective events through dust direct effects by weakening the sea‐breeze circulation.

An analysis of the spatial variation of tropical cyclone rainfall trends in Mainland Southeast Asia

AbstractTropical cyclones (TCs) and the associated rainfall (TCR) have received increasing attention because of their catastrophic damages. Due to the differences in TC characteristics and TCR in different ocean basins, the changes in TCR would be complicated for areas receiving TC landfalling from multi‐basins. Therefore, separating TCR and TC characteristics from the formation basins can offer more insights for accurately evaluating TCR in the landfalling areas. Here we selected the TC‐prone Mainland Southeast Asia (MSEA) to investigate changes in TCR regarding TC characteristics from the surrounding formation basins from 1983 to 2020. Results show that the interannual variability of the total TCs influencing MSEA (MSEA‐ALL‐TC) characteristics, including number, total duration, maximum intensity and accumulated cyclone energy, was dominated by the TCs originating from the Western North Pacific (WNP‐TC). However, the total TCR was controlled by the TCs originating from the WNP and the South China Sea (SCS‐TC), whose influence on TCR was concentrated in the eastern MSEA. TCR associated with TCs originating from the Bay of Bengal was relatively small and concentrated in the western MSEA. For the whole MSEA, the total TCR contributed up to 47% of the annual extreme rainfall amount. Annual TCR presented significant decreasing trends in the southeast MSEA, while increasing trends exist in the northeast. These contrasting trends are attributed to the reduced tendency of WNP‐TC track density and the increased SCS‐TC rainfall rate. We also found that the SCS‐TC induced a higher rainfall rate than the other two basins. The TC characteristics of number, total duration, maximum intensity and accumulated cyclone energy were significantly correlated with TCR in each formation basin, with the highest correlation of the total duration. This study improves our understanding of the influence of changes in TC characteristics on TCR in the TC multi‐source region.

Runoff required to drive postimpact gully development on the walls of Meteor Crater (Arizona, USA)

Since the impact ∼50,000 yr ago, surface runoff has entrained and transported sediment from the walls to the floor of Meteor Crater (Arizona, USA). Previous work interpreted this erosion and deposition to be due to predominantly fluvial (i.e., dilute water transport) processes. However, light detection and ranging (LiDAR)−derived topographic data and field observations indicate that debris flows dominated, which were likely generated by runoff that entrained the talus that borders bedrock cliffs high on the crater walls. The low gradient of the crater floor caused debris flows to stop, leaving lobate deposits, while fluvial processes delivered sediment toward the center of the crater. Cosmogenic radionuclide dating of levee deposits suggests that debris-flow activity ceased in the late Pleistocene, synchronous with regional drying. Assuming a rock-to-water ratio of 0.3 at the time of transport by mass flows, it would have taken ∼2 × 106 m3 of water to transport the estimated ∼6.8 × 106 m3 of debris-flow deposits found at the surface of the crater floor. This extensive erosion would require ∼6 m of total runoff over the 0.35 km2 upslope source area of the crater, or ∼18 mm of runoff per debris-flow event. Much more runoff did occur, as evidenced by crater lake deposits, Holocene fluvial activity (which produced little erosion), and contemporary rainfall rates. Rarely on Earth is the total amount of water that creates and runs through a landscape estimated, yet such calculations are commonly done on Mars. Our analysis suggests that erosional and depositional landforms may record only a small fraction of the total runoff.

Effect of Localised Pressure Depression and Rain on Aerodynamic Characteristics of MALE UAV

This paper presents the effect of the local low-pressure region in the atmosphere and rain on aerodynamiccharacteristics of medium altitude long endurance unmanned aerial vehicle (MALE-UAV) configuration duringcruise/loiter. Computations are performed using CFD++, a commercial CFD software suite. A large low-pressuredepression past the MALE UAV (symmetrically and asymmetrically) with pressure 10 – 15 % lower than the freestream pressure and a widespread rainfall type with a rainfall rate of 1195 mm/hr., are considered for CFD simulation.A large low pressure that spans the whole MALE-UAV results in a decrement in both lift and drag, but does not affect the yawing and rolling moments significantly. However, a low-pressure region that engulfs only one-half of MALE UAV causes sudden/abrupt changes in rolling and yawing moments. The effect of rain causes a significant decrease in a lift at higher alpha, accompanied by a decrease in stall angle of 2 degrees, and a significant increase in drag. From the study, a Standard Operating Procedure (SOP) was adopted to fly UAVs in adverse weather effects,such that the aircraft can be operated with a velocity higher than 1.3Vstall and at a power setting not less than 75% of max power capacity.

Analysis of Madden-Julian Oscillation (MJO) on extreme rainfall event in the west coastal south Sulawesi for mitigation disaster

Madden Julian Oscillation (MJO) is one of the global phenomena that affects weather and climate conditions in Indonesia. MJO increases the rainfall rate and causes a plethora of extreme rainfall occurrences in areas along its trajectory. Those extreme rainfall events could trigger hydrometeorological hazards that endanger the surrounding environment. As the first step to analyse this extreme weather event, this research tries to determine the threshold of the extreme rainfall rate. The method used for determining the threshold is the statistical method 98th percentile. The next step is to identify the frequency trend of the extreme rainfall in the period of 1991 to 2020, by measuring the rainfall rate and comparing it with the normal value. If the rainfall rate is above the normal condition in a certain threshold, then it is considered an extreme rainfall event. After that, these extreme rainfall occurrences are compared to the active MJO phase to find out the influence of MJO to the rainfall in the west coast of South Sulawesi. Then, the dynamical atmospheric conditions are to be analysed during those extreme rainfall events. The result shows that the frequency trend of extreme rainfall events are generally negative in 5 (five) regions, which means an insignificant correlation between MJO and rainfall rate. In contrast, 3 (three) other regions show a positive trend. The influence of an active MJO on the extreme rainfall rate is about 34,1%. Meanwhile, the rest for about 65,9% is influenced by other factors. The use of MJO indices for generating early warning hydrometeorological disasters is by utilising the MJO monitoring data, supported with the analysis of dynamical atmospheric condition in the west coast of South Sulawesi.

A case study of exceptionally heavy rainfall event over Uttarakhand, India on 18th October, 2021 and its forecasting

The unprecedented rainfall observed over Uttarakhand on 18th October 2021 caused landslides, debris flow and floods over the Kumaun region and adjoining districts of the Garhwal region of Uttarakhand, which resulted in huge damage to life, agriculture, transport, tourism and other sectors. The synoptic and dynamic study of the current event showed the movement of the Low-Pressure Area over central India resulting in the strong southeasterly winds (Atmospheric River) over Indo-Gangetic planes from the Bay of Bengal from 17th to 19th October. The interaction and blocking of the Atmospheric River by the deep trough of eastward-moving Western Disturbance (WD) caused extreme rainfall over Uttarakhand. However, the X-band Doppler Weather Radar and 123 Automatic Weather/raingauge Stations data suggest that the hourly rainfall rate was of light to moderate intensity (10-20 mm/h) over most of the area and at most of the time. The rainfall rate was extremely intense (50-100 m/hour) for around 1-hour duration in 7 stations of Udham Singh Nagar, Champawat, Nainital and Pauri districts. Unlike the June 2013 extremely heavy rainfall event over Uttarakhand which impacted the whole Uttarakhand state, the present event was concentrated over the Kumaun region and the highest ever 24-hours accumulated rainfall was observed on 18th October, 2021 in Kumaon region of Uttarakhand. The expected rainfall as well as the impact of the event over Uttarakhand was forecasted 5 days in advance with good accuracy based on the synoptic analysis and NWP model guidance. The predictability of the IMD-GFS (T-1534) NWP model was found to be up to 10 days for this extreme rainfall event.

Early selection for drought tolerance in popcorn based on gene effects estimated in seedlings.

Low rainfall rates are becoming increasingly frequent because of climate change, causing droughts and threatening world food security. For popcorn, drought is the most limiting abiotic factor for plant's growth and development. Thus, the water deficit directly impacts for crop productivity. Based on knowledge of the genetic basis of traits involved in stages of popcorn germination and seedling development under water stress, genotypes with potential for adaptation to adverse growing conditions can be selected early. Therefore, data on genetic effects and combining ability of 10 popcorn parents were compiled to propose breeding strategies for the development of cultivars with greater adaptation to water stress in the early stages. Forty-five diallel hybrids were evaluated under two different water regimes, that is, water stress and full irrigation. This corresponded to a water retention capacity of 25% and 70% of the germination paper. The plants were watered daily as needed for seven days. A range of factors were evaluated, that is, germination traits including the germination speed index and germination on the seventh day; shoot traits including length and dry weight; and root system including length, dry weight, root-to-shoot ratio, maximum root number, root network area, specific and root network length, and root volume. Breeding for drought adaption in the early stages of popcorn development can be successful when hybrids are used, because of the genetic effects of dominance (ϕs). These control the traits evaluated at the seedling stage. The combinations L61 x P2 and L71 x P3 were recommended, in view of the more successful performance estimated for traits related to the shoot and root system.

A case study on the changing pattern of monsoon rainfall duration and its amount during recent five decades in different agroclimatic zones of Punjab state of India

Rainfall is an important part of hydrological cycle and any alteration in its pattern influence water resources. In Punjab, the monsoon season of 77 days extending during three months July, August and September, receives rainfall at an average rate of 6 mm/day. In the present study, monsoon rainfall data for three parts of the state, viz., the north eastern region (1984-2020), Central plain region (1970-2020) and the south western region (1977-2020) of the state have been analyzed using non-parametric tests, i.e., descriptive statistics, trend analysis, Mann Kendall test and Sen’s slope. Though, the duration of the monsoon season has increased over the last two decades at 0.8 day/year, the rate of rainfall has decreased as rainfall has been less than normal during 17 of the past 20 years. The monsoon rainfall analysis for the five decades indicates a significant decrease in rainfall at 0.7 mm/year which has mainly been due to a decline in rainfall in the north eastern region. The Sen’s slope value of -4.77 (Ballowal) and -0.60 (Bathinda) indicate a decreasing trend of rainfall in the region. The decreasing trend in rainfall received during the July-August months with Sen’s slope values ranging between -0.04 to -2.50 and -0.24 to -3.14, indicates that the months which contribute 70 percent to total rainfall are not a good signal for the agriculture sector in the state.

Automatic Detection of Rainfall at Hourly Time Scales from Mooring Near-Surface Salinity in the Eastern Tropical Pacific

Abstract We explore the use of ocean near-surface salinity (NSS), that is, salinity at 1-m depth, as a rainfall occurrence detector for hourly precipitation using data from the Salinity Processes in the Upper-Ocean Regional Studies–2 (SPURS-2) mooring at 10°N, 125°W. Our proposed unsupervised learning algorithm consists of two stages. First, an empirical quantile-based identification of dips in NSS enables us to capture most events with hourly averaged rainfall rate of >5 mm h−1. Overestimation of precipitation duration is then corrected locally by fitting a parametric model based on the salinity balance equation. We propose a local precipitation model composed of a small number of calibration parameters representing individual rainfall events and their location in time. We show that unsupervised rainfall detection can be formulated as a statistical problem of predicting these variables from NSS data. We present our results and provide a validation technique based on data collected at the SPURS-2 mooring. Significance Statement Continuous monitoring of precipitation in the ocean is challenging when a physical rain gauge is not available in the region of interest. Indirect detection of precipitation using available data, such as changes in ocean near-surface salinity (NSS) can be used to construct a virtual rainfall detector. We propose to combine data-based and model-based methods to detect rainfall without the use of a physical rain gauge. We use NSS and precipitation data from a mooring in the eastern tropical Pacific Ocean to develop and test the method.

Rain attenuation prediction model for terrestrial links incorporating wet antenna effects

AbstractAccurate prediction of rain attenuation is critical for the design of terrestrial line‐of‐sight link systems above 5 GHz, particularly for millimetre‐wave frequency. Anomalous behaviour in the adjustment factor in existing rain attenuation prediction models is significantly greater than 1 at short distances and has been reported. To solve this problem and improve the accuracy, a rain attenuation prediction model for terrestrial line‐of‐sight links is proposed. The total rain attenuation described in the model accounts for the contributions of wet antenna attenuation and path rain attenuation. In addition, a rainfall rate adjustment factor is proposed. The proposed model has a root‐mean‐square error of 21.54% in prediction, which is an improvement compared to other existing models. Because the rainfall rate adjustment factor used in the model approaches 1 at short distances, the model can be applied to rain attenuation prediction for short‐distance links. The results will assist designers to design link margins more accurately.

Regression Analysis for Crop Production Using CLARANS Algorithm

Crop production rate relies on rainfall over Rejang Lebong district. Data showed a discrepancy between increased crop production and rainfall in Rejang Lebong District. However, the spatiotemporal distribution of the crop variable's dependencies remains unclear. This study analyses the relationship between rainfall and crop production rate in the Rejang Lebong district based on the performance of the machine learning method. In addition, this research also performed regression analysis to carry out rainfall clusters and crop production. This order provides information in the form of cluster results to determine how much the rainfall variable influences the crop production rate in each cluster. Harnessing the Elbow, CLARANS, Simple Linear Regression, and Silhouette Coefficient methods, this study used 231 rainfall data sourced from the Bengkulu BMKG and 110 data for plant production obtained from BPS Bengkulu Province from 2000-2022. This research found that the optimal clusters were 3 clusters. C1 contains 106 data with the largest regression value for chili = 0.127, C2 contains 15 data with the largest regression value for mustard greens = 0.135, and C3 contains 110 data with the largest regression value for cabbage = 0.408, eggplant = 0.197, and carrots = 0.201. Furthermore, this research also found that the biggest correlation of crops with highly significant improvement would be cabbage commodity (Y=0.4114X+0.2013) and chili plantation with high RSME (0.9897).

UAV Communication Recovery under Meteorological Conditions

Our study proposes a UAV communications recovery strategy under meteorological conditions based on a ray tracing simulation of excessive path loss in four distinct three-dimensional (3D) urban environments. We start by reviewing the air-to-ground propagation loss model under meteorological conditions, as well as the specific attenuation of rain, fog, and snow, and we propose a new expression for line-of-sight (LoS) probability. Using the two frequency bands of 28 GHz and 71 GHz, we investigate the impact of specific attenuation caused by different weather conditions and analyze the relationship between the radius of the UAV coverage area and the elevation angle. Furthermore, we investigate the effects of the rainfall rate, liquid water density, and snowfall rate on the maximum coverage area and optimal height of the UAV. Eventually, we propose a strategy that involves compensating for the maximum path loss and adjusting the UAV’s position to recover the coverage of the UAV to ground users. Our results show that rain has the greatest impact on the UAV’s coverage area and optimum height among the three types of weather conditions. For various weather conditions, relative to Region 1, the percentage reduction in the maximum coverage radius of Region 2 to Region 4 increases gradually, and the extent of each increase is approximately 10%. Moreover, after adding the compensated path loss, the coverage radius of the UAV in the four regions is restored to a value slightly larger than that before the rain. In addition, rain caused the greatest reduction in UAV coverage for suburban environments and the lowest for high-rise urban environments.