Inference of raindrop size distributions from measurements of rainfall rate and attenuation at infrared wavelengths

Radio Science ◽  
1995 ◽  
Vol 30 (4) ◽  
pp. 931-941 ◽  
Author(s):  
A. Maitra ◽  
C. J. Gibbins
Keyword(s):  
Rainfall Rate ◽  
Size Distributions ◽  
Infrared Wavelengths ◽  
Raindrop Size

scholarly journals A Preliminary Analysis of Spatial Variability of Raindrop Size Distributions during Stratiform Rain Events

2009 ◽  
Vol 48 (2) ◽  
pp. 270-283 ◽  
Author(s):  
Choong Ke Lee ◽  
Gyu Won Lee ◽  
Isztar Zawadzki ◽  
Kyung-Eak Kim
Keyword(s):  
Spatial Variability ◽  
Characteristic Number ◽  
Radar Reflectivity ◽  
Rainfall Rate ◽  
Size Distributions ◽  
Number Density ◽  
Ratio Error ◽  
Raindrop Size ◽  
Rain Events ◽  
Highly Correlated

Abstract The spatial variability of raindrop size distributions (DSDs) and precipitation fields is investigated utilizing disdrometric measurements from the four Precipitation Occurrence Sensor Systems (POSS) and radar reflectivity fields from S-band dual-polarization radar and vertically pointing X-band radar. The spatial cross correlation of the moments of DSDs, their ratio, error in rainfall estimate, and normalization parameters are quantified using a “noncentered” correlation function. The time-averaged spatial autocorrelation function of observed radar reflectivity factor (Ze) is smaller than that of estimated rainfall rate from Ze because of power-law R–Z transformation with its exponent larger than unity. The important spatial variability of DSDs and rain integral fields is revealed by the significant differences among average DSDs and leads to an average fractional error of 25% in estimating rainfall accumulation during an event. The spatial correlation of the reflectivity from POSS is larger than that of Ze because of larger measurement noise in Ze. The higher moments of DSDs are less correlated in space than lower moments. The correlation of rainfall estimate error is higher than that of estimated rainfall rate and of rainfall rate calculated from DSDs. The correlation of the characteristic number density is low (0.87 at 1.3-km distance), suggesting that the assumed homogeneity of the characteristic number density in space could result in larger errors in the retrieval of DSDs and rain-related parameters. However, the characteristic diameter is highly correlated in space.

scholarly journals Variability of rainfall rate and raindrop size distributions in heavy rain

2009 ◽  
Vol 45 (4) ◽  
Author(s):  
James A. Smith ◽  
Eric Hui ◽  
Matthias Steiner ◽  
Mary Lynn Baeck ◽  
Witold F. Krajewski ◽  
...  
Keyword(s):  
Heavy Rain ◽  
Rainfall Rate ◽  
Size Distributions ◽  
Raindrop Size

scholarly journals On the Shape–Slope Relation of Drop Size Distributions in Convective Rain

2005 ◽  
Vol 44 (7) ◽  
pp. 1146-1151 ◽  
Author(s):  
Axel Seifert
Keyword(s):  
Size Distribution ◽  
Gamma Distribution ◽  
Drop Size ◽  
Empirical Relation ◽  
Size Distributions ◽  
Shape Parameters ◽  
Raindrop Size Distribution ◽  
Raindrop Size ◽  
Drop Size Distributions ◽  
Good Agreement

Abstract The relation between the slope and shape parameters of the raindrop size distribution parameterized by a gamma distribution is examined. The comparison of results of a simple rain shaft model with an empirical relation based on disdrometer measurements at the surface shows very good agreement, but a more detailed discussion reveals some difficulties—for example, deviations from the gamma shape and the overestimation of collisional breakup.

scholarly journals Reflectivity and Liquid Water Content Vertical Decomposition Diagrams to Diagnose Vertical Evolution of Raindrop Size Distributions

2016 ◽  
Vol 33 (3) ◽  
pp. 579-595 ◽  
Author(s):  
Christopher R. Williams
Keyword(s):  
Water Content ◽  
Liquid Water ◽  
Liquid Water Content ◽  
Doppler Velocity ◽  
Size Distributions ◽  
Vertical Column ◽  
Vertical Decomposition ◽  
Air Motion ◽  
Raindrop Size ◽  
Microphysical Processes

AbstractThis study consists of two parts. The first part describes the way in which vertical air motions and raindrop size distributions (DSDs) were retrieved from 449-MHz and 2.835-GHz (UHF and S band) vertically pointing radars (VPRs) deployed side by side during the Midlatitude Continental Convective Clouds Experiment (MC3E) held in northern Oklahoma. The 449-MHz VPR can measure both vertical air motion and raindrop motion. The S-band VPR can measure only raindrop motion. These differences in VPR sensitivities facilitates the identification of two peaks in 449-MHz VPR reflectivity-weighted Doppler velocity spectra and the retrieval of vertical air motion and DSD parameters from near the surface to just below the melting layer.The second part of this study used the retrieved DSD parameters to decompose reflectivity and liquid water content (LWC) into two terms, one representing number concentration and the other representing DSD shape. Reflectivity and LWC vertical decomposition diagrams (Z-VDDs and LWC-VDDs, respectively) are introduced to highlight interactions between raindrop number and DSD shape in the vertical column. Analysis of Z-VDDs provides indirect measure of microphysical processes through radar reflectivity. Analysis of LWC-VDDs provides direct investigation of microphysical processes in the vertical column, including net raindrop evaporation or accretion and net raindrop breakup or coalescence. During a stratiform rain event (20 May 2011), LWC-VDDs exhibited signatures of net evaporation and net raindrop coalescence as the raindrops fell a distance of 2 km under a well-defined radar bright band. The LWC-VDD is a tool to characterize rain microphysics with quantities related to number-controlled and size-controlled processes.

scholarly journals Estimation of rainfall erosivity based on WRF-derived raindrop size distributions

2020 ◽  
Author(s):  
Qiang Dai ◽  
Jingxuan Zhu ◽  
Shuliang Zhang ◽  
Shaonan Zhu ◽  
Dawei Han ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Water Conservation ◽  
Large Scale ◽  
Weather Prediction ◽  
Wrf Model ◽  
Analysis Data ◽  
Potential Effect ◽  
Rainfall Erosivity ◽  
Size Distributions ◽  
Raindrop Size

Abstract. Soil erosion can cause various ecological problems, such as land degradation, soil fertility loss, and river siltation. Rainfall is the primary water-driving force for soil erosion and its potential effect on soil erosion is reflected by rainfall erosivity that relates to the raindrop kinetic energy (KE). As it is difficult to observe large-scale dynamic characteristics of raindrops, all the current rainfall erosivity models use the function based on rainfall amount to represent the raindrops KE. With the development of global atmospheric re-analysis data, numerical weather prediction (NWP) techniques become a promising way to estimate rainfall KE directly at regional and global scales with high spatial and temporal resolutions. This study proposed a novel method for large-scale and long-term rainfall erosivity investigations based on the Weather Research and Forecasting (WRF) model, avoiding errors caused by inappropriate rainfall–energy relationships and large-scale interpolation. We adopted three microphysical parameterizations schemes (Morrison, WDM6, and Thompson aerosol-aware [TAA]) to obtain raindrop size distributions, rainfall KE and rainfall erosivity, with validation by two disdrometers and 304 rain gauges around the United Kingdom. Among the three WRF schemes, TAA had the best performance compared with the disdrometers at a monthly scale. The results revealed that high rainfall erosivity occurred in the west coast area at the whole country scale during 2013–2017. The proposed methodology makes a significant contribution to improving large-scale soil erosion estimation and for better understanding microphysical rainfall–soil interactions to support the rational formulation of soil and water conservation planning.

scholarly journals Estimation of rainfall erosivity based on WRF-derived raindrop size distributions

2020 ◽  
Vol 24 (11) ◽  
pp. 5407-5422
Author(s):  
Qiang Dai ◽  
Jingxuan Zhu ◽  
Shuliang Zhang ◽  
Shaonan Zhu ◽  
Dawei Han ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Kinetic Energy ◽  
Water Conservation ◽  
Large Scale ◽  
Weather Prediction ◽  
Wrf Model ◽  
Analysis Data ◽  
Rainfall Erosivity ◽  
Size Distributions ◽  
Raindrop Size

Abstract. Soil erosion can cause various ecological problems, such as land degradation, soil fertility loss, and river siltation. Rainfall is the primary water-driven force for soil erosion, and its potential effect on soil erosion is reflected by rainfall erosivity that relates to the raindrop kinetic energy. As it is difficult to observe large-scale dynamic characteristics of raindrops, all the current rainfall erosivity models use the function based on rainfall amount to represent the raindrops' kinetic energy. With the development of global atmospheric re-analysis data, numerical weather prediction techniques become a promising way to estimate rainfall kinetic energy directly at regional and global scales with high spatial and temporal resolutions. This study proposed a novel method for large-scale and long-term rainfall erosivity investigations based on the Weather Research and Forecasting (WRF) model, avoiding errors caused by inappropriate rainfall–energy relationships and large-scale interpolation. We adopted three microphysical parameterizations schemes (Morrison, WDM6, and Thompson aerosol-aware) to obtain raindrop size distributions, rainfall kinetic energy, and rainfall erosivity, with validation by two disdrometers and 304 rain gauges around the United Kingdom. Among the three WRF schemes, Thompson aerosol-aware had the best performance compared with the disdrometers at a monthly scale. The results revealed that high rainfall erosivity occurred in the west coast area at the whole country scale during 2013–2017. The proposed methodology makes a significant contribution to improving large-scale soil erosion estimation and for better understanding microphysical rainfall–soil interactions to support the rational formulation of soil and water conservation planning.

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