Gyu Won Lee

Variability of Drop Size Distributions: Time-Scale Dependence of the Variability and Its Effects on Rain Estimation

Abstract A systematic and intensive analysis is performed on 5 yr of reliable disdrometric data (over 20 000 one-minute drop size distributions, DSDs) to investigate the variability of DSDs in the Montreal, Quebec, Canada, area. The scale dependence (climatological scale, day to day, within a day, between physical processes, and within a physical process) of the DSD variability and its effect on rainfall intensity R estimation from radar reflectivity Z are explored in terms of bias and random errors. Detail error distributions are also provided. The use of a climatological R–Z relationship for rainfall—affected by all of the DSDs’ variability—leads on average to a random error of 41% in instantaneous rain-rate estimation. This error decreases with integration time, but the decrease becomes less pronounced for integration times longer than 2 h. Daily accumulations computed with the climatological R–Z relationship have a bias of 28% because of the day-to-day DSD variability. However, when daily R–Z relation...

Error Statistics of VPR Corrections in Stratiform Precipitation

Abstract Errors in surface rainfall estimates that are caused by ignoring the vertical profile of reflectivity (VPR) and range effects have been assessed by simulating how fine-resolution 3D reflectivity measurements at close ranges are sampled by the radar at various ranges and heights. Uncorrected and corrected accumulations from 33 events of mainly stratiform precipitation, with a recognizable melting layer for over 250 h, have been generated using two basic procedures: (a) the “near range” or “inner” VPR and (b) the intensity-dependent “climatological” VPR. The root-mean-square (rms) error structure has been derived as a function of height and range, for accumulations ranging from 5 min to 2 h, for various brightband heights and verification areas. However, it is the errors along the lowest default height that are most relevant. The stratification of the results by the height of the bright band is essential to understand the influence of the bright band with range. The largest errors (>100% at near ra...

A General Approach to Double-Moment Normalization of Drop Size Distributions

Normalization of drop size distributions (DSDs) is reexamined here. First, an extension of the scaling normalization that uses one moment of the DSD as a scaling parameter to a more general scaling normalization that uses two moments as scaling parameters of the normalization is presented. In addition, the proposed formulation includes all two-parameter normalizations recently introduced in the literature. Thus, a unified vision of the question of DSD normalization and a good model representation of DSDs are given. Data analysis of some convective and stratiform DSDs shows that, from the point of view of the compact representation of DSDs, the double-moment normalization is preferred. However, in terms of physical interpretation, the scaling exponent of the single-moment normalization clearly indicates two different rain regimes, whereas in the double-moment normalization the two populations are not readily separated. It is also shown that DSD analytical models (exponential, gamma, and generalized gamma DSD) have the same scaling properties, indicating that the scaling formalism of DSDs is a very general way of describing DSDs.

Identification and Removal of Ground Echoes and Anomalous Propagation Using the Characteristics of Radar Echoes

Abstract This paper explores the removal of normal ground echoes (GREs) and anomalous propagation (AP) in ground-based radars using a fuzzy logic approach. Membership functions and their weights are derived from the characteristics of radar echoes as a function of radar reflectivity. The dependence on echo intensity is shown to significantly improve the proper identification of GRE/AP. In addition, the proposed method has a better performance at lower elevation angles. The overall performance is comparable with that from a polarimetric approach and can thus be easily implemented in operational radars.

Variability of drop size distributions : Noise and noise filtering in disdrometric data

Abstract Disdrometric measurements are affected by the spurious variability due to drop sorting, small sampling volume, and instrumental noise. As a result, analysis methods that use least squares regression to derive rainfall rate–radar reflectivity (R–Z) relationships or studies of drop size distributions can lead to erroneous conclusions. This paper explores the importance of this variability and develops a new approach, referred to as the sequential intensity filtering technique (SIFT), that minimizes the effect of the spurious variability on disdrometric data. A simple correction for drop sorting in stratiform rain illustrates that it generates a significant amount of spurious variability and is prominent in small drops. SIFT filters out this spurious variability while maintaining the physical variability, as evidenced by stable R–Z relationships that are independent of averaging size and by a drastic decrease of the scatter in R–Z plots. The presence of scatter causes various regression methods to y...

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

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 tha...

An Experimental Study of Small-Scale Variability of Radar Reflectivity Using Disdrometer Observations

Abstract Analysis of data collected by four disdrometers deployed in a 1-km2 area is presented with the intent of quantifying the spatial variability of radar reflectivity at small spatial scales. Spatial variability of radar reflectivity within the radar beam is a key source of error in radar-rainfall estimation because of the assumption that drops are uniformly distributed within the radar-sensing volume. Common experience tells one that, in fact, drops are not uniformly distributed, and, although some work has been done to examine the small-scale spatial variability of rain rates, little experimental work has been done to explore the variability of radar reflectivity. The four disdrometers used for this study include a two-dimensional video disdrometer, an X-band radar-based disdrometer, an impact-type disdrometer, and an optical spectropluviometer. Although instrumental differences were expected, the magnitude of these differences clouds the natural variability of interest. An algorithm is applied to ...

Modeling the variability of drop size distributions in space and time

Abstract The information on the time variability of drop size distributions (DSDs) as seen by a disdrometer is used to illustrate the structure of uncertainty in radar estimates of precipitation. Based on this, a method to generate the space–time variability of the distributions of the size of raindrops is developed. The model generates one moment of DSDs that is conditioned on another moment of DSDs; in particular, radar reflectivity Z is used to obtain rainfall rate R. Based on the fact that two moments of the DSDs are sufficient to capture most of the DSD variability, the model can be used to calculate DSDs and other moments of interest of the DSD. A deterministic component of the precipitation field is obtained from a fixed R–Z relationship. Two different components of DSD variability are added to the deterministic precipitation field. The first represents the systematic departures from the fixed R–Z relationship that are expected from different regimes of precipitation. This is generated using a simp...

Real-Time Comparisons of VPR-Corrected Daily Rainfall Estimates with a Gauge Mesonet

Abstract The relative skill of two vertical-profile-of-reflectivity (VPR) correction techniques for daily accumulations on a selected dataset and a real-time dataset has been verified. The first technique (C1) adjusts the 1-h rainfall amounts already derived on a Cartesian CAPPI map at an altitude of 1.5 km in a “one step” procedure using the range-dependent space–time-averaged VPR over the 1-h interval. The C2 technique corrects the nonconvective polar reflectivity measurements of each 5-min radar cycle that are also centered at a height of 1.5 km according to a VPR that is similarly derived but over a shorter time interval. The results emphasize the importance of applying a VPR correction scheme—in particular, in a climatic regime in which most of the liquid precipitation falls from stratiform echoes. The crucial importance of the choice of datasets is also underlined, causing differences in the final assessment that may be greater than those between the various algorithms. Both techniques perform well ...

Sources of Errors in Rainfall Measurements by Polarimetric Radar: Variability of Drop Size Distributions, Observational Noise, and Variation of Relationships between R and Polarimetric Parameters

Abstract Using a set of long-term disdrometric data and of actual radar measurements from the McGill S-band operational polarimetric radar, several sources of errors in rain measurement with polarimetric radar are explored in order to investigate their relative importance and the feasibility of a polarimetric technique for estimating R in the context of the McGill S-band operational radar that performs a full volume scan of 24 plan position indicators (PPIs) every 5 min. The sources of errors considered are the variability of drop size distributions (DSDs), observational noise, and systematic variation of the relationships between R and polarimetric parameters at different climate regimes. Additional polarimetric parameters dramatically reduce the effect of the DSD variability on rain estimates by radar. The effectiveness of various multiparameter relationships is investigated. The relationships from the literature that are derived from the DSD model and measured DSDs at a different climate regime differ ...