scholarly journals 4-D-VAR assimilation of disdrometer data and radar spectral reflectivities for raindrop size distribution and vertical wind retrievals

2016 ◽  
Vol 9 (7) ◽  
pp. 3145-3163 ◽  
Author(s):  
François Mercier ◽  
Aymeric Chazottes ◽  
Laurent Barthès ◽  
Cécile Mallet
Keyword(s):  
Data Assimilation ◽  
Size Distribution ◽  
Vertical Wind ◽  
Data Sets ◽  
Raindrop Size Distribution ◽  
Raindrop Size ◽  
Microphysical Processes ◽  
Rain Events ◽  
Wind Profiles ◽  
Vertical Winds

Abstract. This paper presents a novel framework for retrieving the vertical raindrop size distribution (DSD) and vertical wind profiles during light rain events. This is also intended as a tool to better characterize rainfall microphysical processes. It consists in coupling K band Doppler spectra and ground disdrometer measurements (raindrop fluxes) in a 2-D numerical model propagating the DSD from the clouds to the ground level. The coupling is done via a 4-D-VAR data assimilation algorithm. As a first step, in this paper, the dynamical model and the geometry of the problem are quite simple. They do not allow the complexity implied by all rain microphysical processes to be encompassed (evaporation, coalescence breakup and horizontal air motion are not taken into account). In the end, the model is limited to the fall of droplets under gravity, modulated by the effects of vertical winds. The framework is thus illustrated with light, stratiform rain events. We firstly use simulated data sets (data assimilation twin experiment) to show that the algorithm is able to retrieve the DSD profiles and vertical winds. It also demonstrates the ability of the algorithm to deal with the atmospheric turbulence (broadening of the Doppler spectra) and the instrumental noise. The method is then applied to a real case study which was conducted in the southwest of France during the autumn 2013. The data set collected during a long, quiet event (6 h duration, rain rate between 2 and 7 mm h−1) comes from an optical disdrometer and a 24 GHz vertically pointing Doppler radar. We show that the algorithm is able to reproduce the observations and retrieve realistic DSD and vertical wind profiles, when compared to what could be expected for such a rain event. A goal for this study is to apply it to extended data sets for a validation with independent data, which could not be done with our limited 2013 data. Other data sets would also help to parameterize more processes needed in the model (evaporation, coalescence/breakup) to apply the algorithm to convective rain and to evaluate the adequacy of the model's parameterization.

scholarly journals 4-D-VAR assimilation of disdrometer data and radar spectral reflectivities for rain drop size distribution and vertical wind retrievals

2015 ◽  
Vol 8 (11) ◽  
pp. 12383-12431
Author(s):  
F. Mercier ◽  
A. Chazottes ◽  
L. Barthès ◽  
C. Mallet
Keyword(s):  
Data Assimilation ◽  
Size Distribution ◽  
Vertical Wind ◽  
Data Sets ◽  
Rain Event ◽  
Data Set ◽  
Light Rain ◽  
Break Up ◽  
Rain Events ◽  
Vertical Winds

Abstract. This paper presents a novel approach for retrieving the vertical raindrop size distribution (DSD) profiles and vertical winds during light rain events. It consists in coupling K band Doppler spectra and ground disdrometer measurements (raindrop fluxes) in a 2-D numerical model propagating the DSD from the clouds to the ground level. The coupling is made via a 4-D-VAR data assimilation algorithm. The model is, up to now, limited to the fall of droplets under gravity, modulated by the effects of vertical winds. Since evaporation, coalescence/break-up and horizontal air motion are not taken into account, we limit the study to light, stratiform rain events in which these phenomena appear negligible. We firstly use simulated data sets (data assimilation twin experiment) to show that the algorithm is able to retrieve the DSD profiles and vertical winds. It also demonstrates the ability of the algorithm to deal with the atmospheric turbulence (broadening of the Doppler spectra) and the instrumental noise. The method is then applied to a real case study which happened in the south-west of France during the autumn 2013. The data set collected during a long, quiet event (6 h duration, rain rate between 2 and 7 mm h−1) comes from an optical disdrometer and a 24 GHz vertically pointing Doppler radar. We show that the algorithm is able to explain the observations and supplies DSD and vertical wind profiles realistic compared to what could be expected for such a rain event. A perspective for this study is to apply it to extended data sets for a more thorough validation. Other data sets would also help to parameterize more phenomena needed in the model (evaporation, coalescence/break-up) to apply the algorithm to convective rain and to evaluate the adequacy of the model's parameterization.

scholarly journals Measurements of Rainfall Velocity and Raindrop Size Distribution Using Coherent Doppler Lidar

2016 ◽  
Vol 33 (9) ◽  
pp. 1949-1966 ◽  
Author(s):  
Makoto Aoki ◽  
Hironori Iwai ◽  
Katsuhiro Nakagawa ◽  
Shoken Ishii ◽  
Kohei Mizutani
Keyword(s):  
Size Distribution ◽  
Wind Velocity ◽  
Vertical Wind ◽  
Doppler Spectrum ◽  
Doppler Lidar ◽  
Stratiform Rain ◽  
Raindrop Size Distribution ◽  
Raindrop Size ◽  
Rain Events ◽  
Vertical Wind Velocity

AbstractRainfall velocity, raindrop size distribution (DSD), and vertical wind velocity were simultaneously observed with 2.05- and 1.54-μm coherent Doppler lidars during convective and stratiform rain events. A retrieval method is based on identifying two separate spectra from the convolution of the aerosol and precipitation Doppler lidar spectra. The vertical wind velocity was retrieved from the aerosol spectrum peak and then the terminal rainfall velocity corrected by the vertical air motion from the precipitation spectrum peak was obtained. The DSD was derived from the precipitation spectrum using the relationship between the raindrop size and the terminal rainfall velocity. A comparison of the 1-min-averaged rainfall velocity from Doppler lidar measurements at a minimum range and that from a collocated ground-based optical disdrometer revealed high correlation coefficients of over 0.89 for both convective and stratiform rain events. The 1-min-averaged DSDs retrieved from the Doppler lidar spectrum using parametric and nonparametric methods are also in good agreement with those measured with the optical disdrometer with a correlation coefficient of over 0.80 for all rain events. To retrieve the DSD, the parametric method assumes a mathematical function for the DSD and the nonparametric method computes the direct deconvolution of the measured Doppler lidar spectrum without assuming a DSD function. It is confirmed that the Doppler lidar can retrieve the rainfall velocity and DSD during relatively heavy rain, whereas the ratio of valid data significantly decreases in light rain events because it is extremely difficult to separate the overlapping rain and aerosol peaks in the Doppler spectrum.

scholarly journals Exploring the use of a column model for the characterization of microphysical processes in warm rain: results from a homogeneous rainshaft model

2007 ◽  
Vol 10 ◽  
pp. 145-152 ◽  
Author(s):  
O. P. Prat ◽  
A. P. Barros
Keyword(s):  
Field Experiments ◽  
Ground Surface ◽  
Cloud Base ◽  
Column Model ◽  
Raindrop Size Distribution ◽  
State Boundary ◽  
Raindrop Size ◽  
Microphysical Processes ◽  
Rain Events ◽  
Rain Rates

Abstract. A study of the evolution of raindrop spectra (raindrop size distribution, DSD) between cloud base and the ground surface was conducted using a column model of stochastic coalescense-breakup dynamics. Numerical results show that, under steady-state boundary conditions (i.e. constant rainfall rate and DSD at the top of the rainshaft), the equilibrium DSD is achieved only for high rain rates produced by midlevel or higher clouds and after long simulation times (~30 min or greater). Because these conditions are not typical of most rainfall, the results suggest that the theoretical equilibrium DSD might not be attainable for the duration of individual rain events, and thus DSD observations from field experiments should be analyzed conditional on the specific storm environment under which they were obtained.

scholarly journals Measurements and Modeling of the Full Rain Drop Size Distribution

Atmosphere ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 39 ◽  
Author(s):  
Merhala Thurai ◽  
Viswanathan Bringi ◽  
Patrick Gatlin ◽  
Walter Petersen ◽  
Matthew Wingo
Keyword(s):  
Size Distribution ◽  
Small Drop ◽  
Dual Frequency ◽  
Raindrop Size Distribution ◽  
Precipitation Estimation ◽  
Rain Drop ◽  
Double Moment ◽  
Raindrop Size ◽  
Microphysical Processes ◽  
Global Precipitation

The raindrop size distribution (DSD) is fundamental for quantitative precipitation estimation (QPE) and in numerical modeling of microphysical processes. Conventional disdrometers cannot capture the small drop end, in particular the drizzle mode which controls collisional processes as well as evaporation. To overcome this limitation, the DSD measurements were made using (i) a high-resolution (50 microns) meteorological particle spectrometer to capture the small drop end, and (ii) a 2D video disdrometer for larger drops. Measurements were made in two climatically different regions, namely Greeley, Colorado, and Huntsville, Alabama. To model the DSDs, a formulation based on (a) double-moment normalization and (b) the generalized gamma (GG) model to describe the generic shape with two shape parameters was used. A total of 4550 three-minute DSDs were used to assess the size-resolved fidelity of this model by direct comparison with the measurements demonstrating the suitability of the GG distribution. The shape stability of the normalized DSD was demonstrated across different rain types and intensities. Finally, for a tropical storm case, the co-variabilities of the two main DSD parameters (normalized intercept and mass-weighted mean diameter) were compared with those derived from the dual-frequency precipitation radar onboard the global precipitation mission satellite.

scholarly journals A Probabilistic View on Raindrop Size Distribution Modeling: A Physical Interpretation of Rain Microphysics

2014 ◽  
Vol 15 (1) ◽  
pp. 427-443 ◽  
Author(s):  
Francisco J. Tapiador ◽  
Ziad S. Haddad ◽  
Joe Turk
Keyword(s):  
Size Distribution ◽  
Regression Line ◽  
Probabilistic Approach ◽  
Sample Variance ◽  
Sample Mean ◽  
Distribution Form ◽  
Raindrop Size Distribution ◽  
Raindrop Size ◽  
Microphysical Processes ◽  
Two Parameters

Abstract The raindrop size distribution (RDSD) is defined as the relative frequency of raindrops per given diameter in a volume. This paper describes a mathematically consistent modeling of the RDSD drawing on probability theory. It is shown that this approach is simpler than the use of empirical fits and that it provides a more consistent procedure to estimate the rainfall rate (R) from reflectivity (Z) measurements without resorting to statistical regressions between both parameters. If the gamma distribution form is selected, the modeling expresses the integral parameters Z and R in terms of only the total number of drops per volume (NT), the sample mean [m = E(D)], and the sample variance [σ2 = E(m − D)2] of the drop diameters (D) or, alternatively, in terms of NT, E(D), and E[log(D)]. Statistical analyses indicate that (NT, m) are independent, as are (NT, σ2). The Z–R relationship that arises from this model is a linear R = T × Z expression (or Z = T−1R), with T a factor depending on m and σ2 only and thus independent of NT. The Z–R so described is instantaneous, in contrast with the operational calculation of the RDSD in radar meteorology, where the Z–R arises from a regression line over a usually large number of measurements. The probabilistic approach eliminates the need of intercept parameters N0 or , which are often used in statistical approaches but lack physical meaning. The modeling presented here preserves a well-defined and consistent set of units across all the equations, also taking into account the effects of RDSD truncation. It is also shown that the rain microphysical processes such as coalescence, breakup, or evaporation can then be easily described in terms of two parameters—the sample mean and the sample variance—and that each of those processes have a straightforward translation in changes of the instantaneous Z–R relationship.

scholarly journals Small-Scale Variability of the Raindrop Size Distribution and Its Effect on Areal Rainfall Retrieval

2016 ◽  
Vol 17 (7) ◽  
pp. 2077-2104 ◽  
Author(s):  
Timothy H. Raupach ◽  
Alexis Berne
Keyword(s):  
Size Distribution ◽  
Drop Size ◽  
Integration Time ◽  
Small Scale ◽  
Drop Diameter ◽  
Weather Model ◽  
Raindrop Size Distribution ◽  
Areal Rainfall ◽  
Raindrop Size ◽  
Microphysical Processes

Abstract The drop size distribution (DSD) describes the microstructure of liquid precipitation. The high variability of the DSD reflects the variety of microphysical processes controlling raindrop properties and affects the retrieval of rainfall. An analysis of the effects of DSD subgrid variability on areal estimation of precipitation is presented. Data used were recorded with a network of disdrometers in Ardèche, France. DSD variability was studied over two typical scales: 5 km × 5 km, similar to the ground footprint size of the Global Precipitation Measurement (GPM) spaceborne weather radar, and 2.8 km × 2.8 km, an operational pixel size of the Consortium for Small-Scale Modeling (COSMO) numerical weather model. Stochastic simulation was used to generate high-resolution grids of DSD estimates over the regions of interest, constrained by experimental DSDs measured by disdrometers. From these grids, areal DSD estimates were derived. The error introduced by assuming a point measurement to be representative of the areal DSD was quantitatively characterized and was shown to increase with the size of the considered area and with drop size and to decrease with the integration time. The controlled framework allowed for the accuracy of retrieval algorithms to be investigated. Rainfall variables derived by idealized simulations of GPM- and COSMO-style algorithms were compared to subgrid distributions of the same variables. While rain rate and radar reflectivity were well represented, the estimated drop concentration and mass-weighted mean drop diameter were often less representative of subgrid values.

scholarly journals Statistical Characteristics of Raindrop Size Distribution in Southwest Monsoon Season

2008 ◽  
Vol 47 (2) ◽  
pp. 576-590 ◽  
Author(s):  
N. V. P. Kirankumar ◽  
T. Narayana Rao ◽  
B. Radhakrishna ◽  
D. Narayana Rao
Keyword(s):  
Size Distribution ◽  
Case Studies ◽  
Monsoon Season ◽  
Parameter Distribution ◽  
Convective Rain ◽  
Raindrop Size Distribution ◽  
Precipitation Regimes ◽  
Raindrop Size ◽  
Microphysical Processes ◽  
Vertical Variability

Abstract Raindrop size distribution (DSD) parameters are retrieved from dual-frequency (UHF and VHF) wind profiler measurements made at Gadanki, India, in a summer monsoon season. The convoluted UHF spectra are first corrected for vertical air motion and spectral broadening (using VHF measurements) and later are used for deriving DSD parameters. Two distinctly different case studies, a mesoscale convective system and a pure stratiform precipitation system, have been considered for a detailed study. DSD parameters obtained in these case studies reveal systematic variations of DSD from case to case and also from one rain regime to another within the same precipitating system. A statistical study has been carried out using the profiler data collected during the passage of 16 rain events. The retrieved DSD profiles are divided into separate rain regimes (stratiform and convection), based on reflectivity, to examine salient microphysical characteristics and the vertical variability of DSD in different precipitation regimes. The distribution of DSD parameters is, in general, wider in the convective rain regime than in the stratiform regime, particularly below 2.4 km. The vertical variation of the gamma parameter distribution in the stratiform rain regime is minimal, indicating that the microphysical processes (growth and decay), which alter the rain DSD, may be in equilibrium. On the other hand, the distribution in the convective rain regime appears to be more complex, with the mean profile of the shape parameter varying significantly with height. The observed vertical variability of the gamma parameters and the median volume diameter in the convective rain regime is attributed to two major microphysical processes: evaporation and breakup. The role of other processes, like drop sorting and collision–coalescence, in altering the DSD parameters is also discussed. The present statistics, representing continental monsoon rainfall, are compared with the existing statistics at Darwin, Australia, and the results are discussed in light of DSD differences in oceanic and continental monsoon precipitation.

scholarly journals Microphysical features of typhoon and non-typhoon rainfall observed in Taiwan, an island in the northwestern Pacific

2021 ◽  
Vol 25 (7) ◽  
pp. 4025-4040
Author(s):  
Jayalakshmi Janapati ◽  
Balaji Kumar Seela ◽  
Pay-Liam Lin ◽  
Meng-Tze Lee ◽  
Everette Joseph
Keyword(s):  
Geographical Location ◽  
Weather Conditions ◽  
Rainfall Rate ◽  
Northwestern Pacific ◽  
Rainfall Erosivity ◽  
Data Sets ◽  
Estimation Algorithms ◽  
Raindrop Size Distribution ◽  
Raindrop Size ◽  
Microphysical Processes

Abstract. Information about the raindrop size distribution (RSD) is vital for comprehending the precipitation microphysics, improving the rainfall estimation algorithms, and appraising the rainfall erosivity. Previous research has revealed that the RSD exhibits diversity with geographical location and weather type, which leads to the assessment of the region and weather-specific RSDs. Based on long-term (2004 to 2016) disdrometer measurements in northern Taiwan, this study attempts to demonstrate the RSD aspects of summer seasons that were bifurcated into two weather conditions, namely typhoon (TY) and non-typhoon (NTY) rainfall. The results show a higher concentration of small drops and a lower concentration of large-sized drops in TY compared to NTY rainfall, and this behavior persisted even after characterizing the RSDs into different rainfall rate classes. RSDs expressed in gamma parameters show higher mass-weighted mean diameter (Dm) and lower normalized intercept parameter (Nw) values in NTY than TY rainfall. Moreover, sorting these two weather conditions (TY and NTY rainfall) into stratiform and convective regimes revealed a larger Dm in NTY than in TY rainfall. The RSD empirical relations used in the valuation of rainfall rate (Z–R, Dm–R, and Nw–R) and rainfall kinetic energy (KE–R and KE–Dm) were enumerated for TY and NTY rainfall, and they exhibited profound diversity between these two weather conditions. Attributions of RSD variability between the TY and NTY rainfall to the thermodynamical and microphysical processes are elucidated with the aid of reanalysis, remote sensing, and ground-based data sets.

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