Isztar Zawadzki

Long-Term Radar Observations of the Melting Layer of Precipitation and Their Interpretation

Abstract In this study, 600 h of vertically pointing X-band radar data and 50 h of UHF boundary layer wind profiler data were processed and analyzed to characterize quantitatively the structure and the causes of the radar signature from melting precipitation. Five classes of vertical profiles of reflectivity in rain were identified, with three of them having precipitation undergoing a transition between the solid and liquid phase. Only one of them, albeit the most common, showed a radar brightband signature. In-depth study of the bright band and its dependence on precipitation intensity reveals that the ratio of the brightband peak reflectivity to the rainfall reflectivity is constant at 8 dB below 0.5 mm h−1 and then increases to reach 13 dB at 2.5 mm h−1 and 16 dB at 5 mm h−1. The equivalent reflectivity factor of snow just above the melting layer is on average 1–2 dB below the reflectivity of rain just below the melting layer, independent of precipitation intensity. The classical brightband explanation...

Biogenic and Anthropogenic Sources of Ice-Forming Nuclei: A Review

Abstract To develop theories and numerical models of the formation and microstructure of clouds and precipitation, it is necessary to identify the potential sources of ice nuclei in the atmosphere. However, the subject remains an area of debate. According to the most accepted theory, the great majority of atmospheric ice nuclei constitute soil mineral particles. But some evidence appears to favor the hypothesis of a nonnegligible contribution to the population of effective ice nuclei made by biogenic material, living or dead. Moreover, some specific human activities have been identified as prolific sources of particles on which ice crystals can be generated. In contrast, it has also been suggested that some anthropogenic effluents deactivate nuclei naturally occurring in the atmosphere. This paper summarizes present knowledge about the biogenic and anthropogenic sources of atmospheric ice nuclei. Recent research reveals an increasingly greater variety of sources and activities of ice nuclei. However intri...

On the Extraction of Near-Surface Index of Refraction Using Radar Phase Measurements from Ground Targets

The authors consider the simplest radar equation involving the index of refraction n: the time t taken by electromagnetic waves to reach a target at range r and return to the radar is r=2rn/c/sub 0/, with c/sub 0/, being the speed of light in a vacuum. For fixed targets, r is constant and only n varies; hence if t could be measured precisely for such targets, the average value of the refractive index over the path between the radar and these targets could be determined. Unfortunately, most radars cannot measure t and site surveys are not accurate enough to determine r with the part-per-million accuracy required to obtain useful information about n. However, if the range to the target is fixed, but only known to a fair accuracy, say better than 1%, it would be enough to allow us to relate changes in t to changes in n; the absolute calibration would then have to be done by other means. With this scheme, we are only required to determine changes in t that can be obtained by measuring the phase of the target.

Instrumental Uncertainties in Z–R Relations

Abstract Intercomparisons among three different sensors for ground-based measurement of drop size distributions are presented: the Joss–Waldvogel distrometer, the optical spectro-pluviometer, and the precipitation occurrence sensor system. Data corresponding to stratiform, continental rain are analyzed, and reflectivity factor–rain rate at the ground (Z–R) relationships are obtained from simultaneous measurements by the three sensors. The Z–R relations derived from the three sensors show differences comparable to the ones seen in distinct climatic regions. In addition, the Z–R relationships are found to be sensitive to the data analysis method.

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...

Modeling of the melting layer. Part I : Dynamics and microphysics

Abstract To obtain the full description of the dynamical and microphysical finescale structures required for the computation of the radar-derived brightband parameters, a numerical model has been developed. A bulk microphysics module was introduced into a nonhydrostatic, fully compressible dynamic framework. A microphysical parameterization scheme, with five water categories (vapor, cloud water, snow, melting snow, and rain), describes the interactions related to the evolution of the melting layer (melting and diffusional exchanges of mass of each hydrometeor category). Dynamic, thermodynamic, and microphysical processes are fully coupled. The main characteristics of the bulk parameterization scheme for melting of snow are the following: 1) wet snow is described by its water content and by an additional prognostic variable, namely, the diameter of the smallest snowflake not yet completely melted; 2) the fall velocity of the melting snowflakes is based on the laboratory observations; and 3) a size-dependen...

Predictability of Precipitation from Continental Radar Images. Part III: Operational Nowcasting Implementation (MAPLE)

Filtering of nonpredictable scales of precipitation can be used to improve forecast precision (rms). Previous papers have studied the scale dependence of predictability of patterns of instantaneous rainfall rate and of probabilistic forecasts. In this paper, motivated by the often localized, intermittent nature of rainfall, the wavelet transform is used to develop measures of predictability at each scale. These measures are then used to design optimal forecast filters. This method is applied to radar composites of rainfall reflectivity over much of the continental United States and is developed to be appropriate for operational forecasts of rainfall rates and raining areas. For the four precipitation events studied, the average correlation at 4-h lead time was increased from 0.50 for the original nowcasts to 0.62 with forecast filtering. This forecast filtering is incorporated into the McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation (MAPLE), which now includes variational echo tracking, a semi-Lagrangian advection scheme, scale-based filtering, and appropriate rescaling of the filtered nowcast fields.

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...

Use of NWP for Nowcasting Convective Precipitation: Recent Progress and Challenges

Traditionally, the nowcasting of precipitation was conducted to a large extent by means of extrapolation of observations, especially of radar ref lectivity. In recent years, the blending of traditional extrapolation-based techniques with high-resolution numerical weather prediction (NWP) is gaining popularity in the nowcasting community. The increased need of NWP products in nowcasting applications poses great challenges to the NWP community because the nowcasting application of high-resolution NWP has higher requirements on the quality and content of the initial conditions compared to longer-range NWP. Considerable progress has been made in the use of NWP for nowcasting thanks to the increase in computational resources, advancement of high-resolution data assimilation techniques, and improvement of convective-permitting numerical modeling. This paper summarizes the recent progress and discusses some of the challenges for future advancement.

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.