Search or ask a question

Is Rain from differential phase shift depends on drop size distribution?

Pulse-Doppler radar

Space-time adaptive processing

Best insight from top research papers

Yes, the differential phase shift (Kdp) of rain does depend on the drop size distribution (DSD) . The relationship between Kdp and DSD is studied using various radar algorithms and simulated data . Different estimation algorithms for Kdp are tested, and their accuracy is analyzed using realistic simulated fields of DSD . The quality of Kdp estimates is evaluated, and the mean normalized absolute error in the estimation of Kdp is determined . X-band polarimetric radar is used to retrieve the rain rate from Kdp, and the variability of this relationship is studied . The error in rain rate estimation due to assumptions about DSD, such as the gamma distribution, is evaluated . The retrieval of DSD parameters from radar measurements is also examined, and the sensitivity of the method to errors in Kdp is analyzed .

Answers from top 4 papers

PDF

Open Access

More filters

Papers (4)	Insight
Journal Article•DOI Comparison of Two Raindrop Size Distribution Retrieval Algorithms for X-Band Dual Polarization Observations Marios N. Anagnostou, Emmanouil N. Anagnostou, Jothiram Vivekanandan, Fred L. Ogden - Show less +3 more 01 Jun 2008-Journal of Hydrometeorology 29 Citations	The paper does not directly mention whether rain from differential phase shift depends on drop size distribution.
Journal Article•DOI Rain drop size distribution variability and impact on X-band polarimetric radar retrieval: Results from the AMMA campaign in Benin Marielle Gosset, Eric-Pascal Zahiri, Sounmaïla Moumouni - Show less +2 more 01 Jan 2010-Quarterly Journal of the Royal Meteorological Society 40 Citations	The paper does not directly answer the question of whether rain from differential phase shift depends on drop size distribution. The paper discusses the use of differential phase shift (KDP) to retrieve rain rate and mentions that KDP is derived from the measured path-integrated phase shift (phDP). However, it does not explicitly mention the dependence of KDP on drop size distribution.
Journal Article•DOI Accuracy of Phase-Based Algorithms for the Estimation of the Specific Differential Phase Shift Using Simulated Polarimetric Weather Radar Data Jacopo Grazioli, Marc Schneebeli, Alexis Berne - Show less +2 more 01 Apr 2014-IEEE Geoscience and Remote Sensing Letters 14 Citations	Yes, the specific differential phase shift (Kdp) is dependent on the drop size distribution (DSD). Kdp is used in quantitative precipitation estimation, hydrometeor classification, DSD retrieval, and microphysical studies of solid precipitation (as mentioned in the abstract).
Open access•DOI The effects of temporal variability of DSD features on pseudo-radar algorithms Auguste Gires, Ioulia Tchiguirinskaia, Daniel Schertzer - Show less +2 more 01 Jan 2019	The paper investigates the relationship between rainfall and differential phase shift (Kdp) using pseudo-radar data. It does not explicitly mention whether Kdp depends on drop size distribution.

My columns

Related Questions

How to test the accuracy of a raindrop sensor?5 answersTo test the accuracy of a raindrop sensor, various methods can be employed based on the design and purpose of the sensor. One approach involves using a rainfall simulator to analyze the sensor's stability and accuracy, followed by predicting rainfall intensity using tools like the Kalman filter. Additionally, intercomparing different types of rain measurement instruments within a specific area can help assess the inherent measurement uncertainties and accuracy levels of the sensors. Another method includes utilizing a raindrop strike kinetic energy test system based on a multi-point PVDF piezoelectric thin film sensor, allowing for fast and accurate raindrop kinetic energy measurements with real-time multi-point capabilities. These diverse testing methodologies provide insights into the accuracy and reliability of raindrop sensors for various applications.

What is the relationship between rainfall and fire frequencies?4 answersFire frequencies are influenced by rainfall patterns. In areas with extreme annual rainfall events, large wildfires tend to occur two years after these events. In the Australian wet-dry tropics, fire frequency is highest in areas where intermediate annual rainfall and strong seasonality in rainfall coincide. In the north-eastern Simpson Desert, wildfires occurred in years with higher rainfall, and a large wildfire reburned areas that had not burned since a previous wildfire in 1975. In the Andean grasslands and montane forests of north-western Argentina, fire occurrence during the winter dry season is influenced by above-average moisture availability in the preceding years. In the Miombo woodlands of northern Mozambique, fire frequency is influenced by land cover, annual rainfall, and other environmental factors.

What are the factors that affect leaf drop?3 answersFactors affecting leaf drop include the positioning of leaves, leaf age, tree vigor, and interactions between temperature and light intensity. In addition, the wettability of plants, leaf inclination angle, and the ability of leaves to respond elastically to drop impact can also influence leaf drop. Furthermore, the type of host plant, such as woody versus herbaceous plants, can affect dropping behavior in leaf-eating insects, particularly in larvae. The wettability and surface structure of leaves, including the presence of trichomes, also play a role in water drop splash and subsequent leaf drop.

What is the current research trend on the effect of raindrop size distribution to mm-wave propagation in wireless telecommunication?5 answersResearch on the effect of raindrop size distribution on mm-wave propagation in wireless telecommunication is currently focused on several key areas. One area of research is the measurement and analysis of rain attenuation and its impact on signal quality and link availability. Studies have been conducted using real measurement data collected from outdoor microcellular systems in Malaysia. Another area of research is the development and evaluation of models for estimating rainfall rates based on local rain drop size distribution (DSD) information. These models aim to improve the accuracy of calculating rainfall rates from microwave or millimeter-wave communication links. Additionally, research has been conducted to study the impact of rain on wave attenuation at different frequencies, such as millimeter wave (77 GHz) and low-terahertz (300 GHz) frequencies. The analysis of raindrop size distributions (DSDs) has also been used to estimate rain attenuation and its effects on mmWave links. Overall, the current research trend is focused on understanding and mitigating the effects of raindrop size distribution on mm-wave propagation in wireless telecommunication.

What is the effect of drop size distributions in two-phase flow on the droplet breakup?1 answersThe effect of drop size distributions in two-phase flow on droplet breakup is influenced by various factors. The critical point at which the breakup mechanism changes depends on the drop size. The droplet/carrier density ratio also plays a role in determining the critical Weber numbers for breakup and bursting/stripping transition. In the presence of emulsifiers, the viscoelastic properties of the droplet interface can affect droplet breakup dynamics. The number fraction of drops that break up in a rotating disc contactor during mass transfer can be used to estimate the effective interfacial tension. Different breakup types and coalescences contribute to equilibrium raindrop size distributions, with filament breakup affecting small-drop peaks and sheet breakup affecting medium-drop peaks. Overall, the drop size distribution in two-phase flow can impact the breakup mechanism and the resulting droplet size distribution.

What are the fundamental mechanisms that govern droplet dynamics in two-phase flow?5 answersThe fundamental mechanisms that govern droplet dynamics in two-phase flow include factors such as capillarity, viscosity, wettability, and surface tension. These factors interact to determine the behavior of droplets in different flow regimes. The dynamics of droplets can be influenced by the distribution of liquid-liquid two-phase flow in microchannels, as well as the stability and uniformity of droplets. In addition, the flow through porous media can lead to the formation of drops and fingers, which affects macroscopic properties such as effective permeability. The interaction between droplets and the main carrying flow in rotating flows also plays a significant role in droplet dynamics, leading to stretching, shrinking, rotating, and dilatation of droplets. These findings provide insights into the physics of droplet behavior and have implications for various applications such as microfluidics and droplet dispensing systems.

See what other people are reading

What are the current research gaps in rainfall frequency?

Current research gaps in rainfall frequency analysis include the lack of understanding regarding the impact of spatiotemporal rainfall heterogeneity on frequency estimates. Additionally, there is a need for rational methods to evaluate the effectiveness of acoustic enhancement of rainfall in field experiments. The existing literature highlights the challenges in assessing the extent of rainfall assumed by information receivers when qualitative terms like "heavy rain" are used, indicating a gap in distinguishing different rainfall amounts through qualitative language. Furthermore, the discrepancies between sub-daily and daily rainfall extremes suggest a gap in accurately detecting time trends in rainfall frequency, emphasizing the challenge posed by changing measurement properties in radar rainfall data sets. Addressing these gaps is crucial for advancing our understanding of rainfall frequency dynamics.What are the current drought situation in Thailand?

The current drought situation in Thailand is increasingly severe, largely attributed to climate change, which has led to a pressing need for the development of a reliable Drought Monitoring and Early Warning System (DMEWS). This system aims to enhance the country's resilience by providing stakeholders with relevant drought indicators that reflect tangible impacts on the ground. Research has utilized a combination of correlation analysis and machine learning techniques, specifically random forest models, to study the relationship between meteorological drought indicators and high-resolution remote sensing vegetation indices. These indices serve as proxies for assessing impacts on crop yield and forest growth, revealing that the connection between drought indicators and impacts varies by land use, season, and region. In the eastern region of Thailand, drought disasters are occurring with greater frequency, with a long-term trend of decreasing rainfall, exacerbating the challenges faced by agriculture. Similarly, in the Lower Northern part of Thailand, a consistent reduction in annual rainfall has been observed, alongside an increase in temperature, contributing to drier conditions. The agricultural sector, a significant part of Thailand's economy, has been notably affected, with drought conditions leading to missed opportunities for exporting agricultural products. The northeastern region, in particular, has been heavily impacted, where farming is a primary livelihood. Analysis using data from the Terra Modis satellite has effectively identified patterns of drought-prone areas, underscoring the extensive reach of drought across the country. This situation underscores the critical importance of investing in advanced monitoring and predictive technologies to mitigate the impacts of drought. The integration of detailed knowledge of crop- and region-specific drought indicators into DMEWS can guide targeted mitigation actions, not only within Thailand but potentially in other parts of Southeast Asia.What are the potential disadvantages of using Radolan Redproc radar data for precipitation monitoring?

Using Radolan Redproc radar data for precipitation monitoring may present certain disadvantages. The radar-based quantitative precipitation estimates (QPE) from Radolan Redproc tend to underestimate total precipitation sums and high-intensity rainfall, requiring thorough quality checks due to systematic and random biases. Additionally, the dataset may have uncertainties and errors that need to be addressed through bias adjustment and verification with ground-truth rain gauge records. Furthermore, the Radolan Redproc radar data may suffer from range-dependent attenuation, which can impact the accuracy of the precipitation estimates. These limitations highlight the importance of ensuring the reliability and quality of Radolan Redproc radar data for effective precipitation monitoring applications.Is there an existing study about integration of rainwater with GIS and Epanet?

The integration of rainwater harvesting (RWH) techniques with Geographic Information Systems (GIS) and hydrological modeling tools like EPANET is a growing area of research, aimed at addressing water scarcity issues, particularly in arid and semi-arid regions. While the provided contexts do not explicitly mention a study that combines RWH, GIS, and EPANET together, they collectively highlight the importance of utilizing GIS and hydrological models in the planning, analysis, and optimization of RWH systems, which could be complementary to the capabilities of EPANET in simulating water distribution networks. For instance, studies have utilized GIS for identifying suitable RWH sites based on various criteria such as land use, soil texture, and slope, demonstrating GIS's critical role in the preliminary stages of RWH planning. Similarly, the application of GIS in analyzing rooftop rainwater harvesting systems and artificial recharge wells indicates its utility in assessing the potential of RWH systems for augmenting water supplies. The development and application of hydrological models, as seen in the distributed rainfall-runoff model for flood simulations, further underscore the potential for integrating such models with GIS for enhanced water resource management. Moreover, the use of GIS and remote sensing for selecting optimal sites for RWH in arid regions, and the integration of the Soil and Water Assessment Tool (SWAT) with GIS for evaluating RWH potential, suggest a methodological framework that could be adapted for incorporating EPANET for detailed water distribution analysis. Although EPANET is specifically designed for simulating water distribution piping systems, its integration with GIS-based RWH site selection and hydrological modeling could offer a comprehensive approach for designing and managing RWH systems, ensuring efficient water distribution and utilization. Therefore, while direct references to studies integrating RWH with both GIS and EPANET are not provided in the contexts, the existing research underscores the feasibility and potential benefits of such an integrated approach for sustainable water resource management.What is Side Looking Airborne Radar?

Side Looking Airborne Radar (SLAR) is a radar system used in aircraft for imaging the ground surface from the side. It has applications in radar location, radio navigation, and target detection. SLAR systems utilize beams that are formed by the radar antenna to receive reflected signals from the Earth's surface, allowing for the determination of angles and boundaries of scanned areas. The technology involves processing techniques like Space-Time Adaptive Processing (STAP) to enhance clutter suppression and target detection performance. Additionally, SLAR systems consider factors such as aircraft altitude, roll, and yaw angles to determine the effective antenna beam width and swath boundaries. These systems play a crucial role in surveillance, reconnaissance, and mapping tasks.How does the CHIRPS rainfall dataset compare with other rainfall datasets in terms of coverage and reliability?

The CHIRPS rainfall dataset is compared with other datasets in terms of coverage and reliability. A study in India found that CHIRPS overestimated rainfall erosivity on the Loess Plateau by 44%, indicating potential reliability issues. In contrast, the GPM dataset performed well in India at various spatial and temporal resolutions, suggesting good coverage and reliability for hydrologic applications. Additionally, a study merging CHIRP estimates with ground measurements showed improved accuracy, highlighting the importance of combining algorithms to enhance reliability. Furthermore, in the Upper Chicamocha River basin, CHIRPS overestimated rainfall, while TerraClimate exhibited overestimation of inter-annual variability, indicating potential coverage challenges in complex terrains. Overall, while CHIRPS shows some reliability issues, combining datasets and considering local validation can enhance coverage and reliability in rainfall estimation.How to test the accuracy of a raindrop sensor?

To test the accuracy of a raindrop sensor, various methods can be employed based on the design and purpose of the sensor. One approach involves using a rainfall simulator to analyze the sensor's stability and accuracy, followed by predicting rainfall intensity using tools like the Kalman filter. Additionally, intercomparing different types of rain measurement instruments within a specific area can help assess the inherent measurement uncertainties and accuracy levels of the sensors. Another method includes utilizing a raindrop strike kinetic energy test system based on a multi-point PVDF piezoelectric thin film sensor, allowing for fast and accurate raindrop kinetic energy measurements with real-time multi-point capabilities. These diverse testing methodologies provide insights into the accuracy and reliability of raindrop sensors for various applications.Which study mentioned about seasonal trend of extreme rainfall in central europe?

The study by Zeder and Fischer focused on the seasonal trend of extreme rainfall in Central Europe. They analyzed long-term daily precipitation records from a densely sampled station network across Austria, Switzerland, Germany, and the Netherlands to relate observed changes in extreme precipitation to the large-scale thermodynamic state of the atmosphere. Their findings indicated an overall intensification and positive scaling signal with Northern Hemispheric temperature in annual, summer, and winter single-day to monthly maximum precipitation. While the scaling magnitudes varied considerably between seasons and subregions, the study highlighted the significant relationship between extreme precipitation and seasonal variations in temperature. This research sheds light on the complex interplay between extreme rainfall events and seasonal trends in Central Europe.Why high temporal resolution rainfall data is needed in the philippines?

High temporal resolution rainfall data is crucial in the Philippines due to the increased frequency of extreme weather events like typhoons. Traditional instruments like rain gauges and ground-based radar have limitations in accurately measuring heavy precipitation, especially in remote areas with uneven distribution. Satellite precipitation datasets (SPDs) such as IMERG, GSMaP, and PERSIANN provide integrated spatial coverage, offering a solution to this challenge. These datasets help in detecting rainfall under various wind speeds and terrains, aiding in better understanding and forecasting of typhoon-related heavy precipitation events. The high temporal resolution of these datasets allows for sub-daily assessments, enabling more accurate monitoring and prediction of rainfall patterns during typhoons, essential for effective water resource and disaster mitigation management in the Philippines.How does the GRACE satellite works?

The Gravity Recovery And Climate Experiment (GRACE) satellite mission, launched in 2002, monitors Earth's gravitational field with high precision, detecting changes in water mass distribution. GRACE observations are used to estimate terrestrial water storage anomalies (TWSA) globally. These anomalies are crucial for various applications, such as forecasting streamflow in mountainous regions, aiding in water resource management. GRACE data also help in studying high-frequency hydro-meteorological fluxes over continents, providing insights into atmospheric reanalyses and weather system persistence. By utilizing GRACE gravity field changes, researchers can assess net flux imbalances in atmospheric processes, contributing to a better understanding of Earth's hydrological cycle and climate dynamics. Overall, GRACE satellites play a vital role in monitoring water storage variations, aiding in climate change studies and enhancing our understanding of Earth's complex systems.What are the primary functions of air radar in detecting and tracking aircraft?

Airborne radars serve crucial functions in military air operations by detecting aircraft at long distances. These radars are equipped with transmit and receive antenna modules that form beams for target detection, enabling functions like sense-and-avoid capabilities. The radar devices emit microwave signals, receive reflections, and use computation means to adjust antenna beams for tracking targets within specific angular sectors. Additionally, radar systems transmit RF waves with dual waveforms, including sinusoids and pulse types, to detect targets based on reflected signals, relative target speed, and carrier speed. Overall, air radars play a vital role in detecting aircraft, tracking targets, and providing essential information to air traffic control centers and onboard control devices.