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  • Author or Editor: I. Zawadzki x
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V. Chandrasekar
,
R. Meneghini
, and
I. Zawadzki

Abstract

Radars have played an important role in the observation of precipitation and will continue to do so in the future. With the recent introduction of space-based radar for measuring precipitation on the Tropical Rainfall Measurement Mission (TRMM) satellite, weather radar applications now range from local to global scales. The radar basis for characterizing precipitation lies in the scattering and propagation properties of electromagnetic waves through precipitation, and is summarized in this paper. The methodologies for converting the backscattering and propagation measurements such as radar reflectivity, differential reflectivity, differential propagation phase, and attenuation to precipitation estimates are provided for both ground-based and space-based radars. Quantitative precipitation estimation has been a challenging problem for over four decades. This challenge has inspired extensive progress in the area of precipitation microphysics, remote sensing techniques, and in situ observations. Another major advance in quantitative precipitation estimation is the understanding of the critical role player by practical engineering considerations. Techniques for developing precipitation algorithms from space and ground observations as well as strategies for validating the estimates are also presented. Following a summary of the various challenges, the discussion focuses on those areas with potential for significant future progress for the estimation of both local and global precipitation.

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I. Zawadzki
,
E. Monteiro
, and
F. Fabry

Abstract

A model of rain development based on the quasi-stochastic coalescence equation and including the sedimentation of drops has been used to study the formation of drop size distributions in conditions of weak updraft. Comparisons with “box model” results indicate that sedimentation effects are crucial in establishing the shapes of the distribution. Under realistic conditions of cloud droplet distribution with size, the raindrop size distributions as simulated by the model compare well with observations of orographic rain made in Hawaii. On the other hand, Doppler radar measurements of drop size distributions just below a bright band confirm that the Marshall-Palmer distribution results from processes affecting particles in the solid phase rather than from the interaction of raindrops.

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I. Zawadzki
,
E. Torlaschi
, and
R. Sauvageau

Abstract

Soundings. surface pressure, temperature and humidity obtained from a standard observation network were correlated with rain rates given by raingages and radar. The correlations indicate that a single thermodynamic parameter (static potential energy) explains ∼60% of the storm-to-storm variability of the mean and the maximum rain rates. During the evolution of a precipitating system the time variation of rain rate parameters follows closely the variation of the static energy. The entire distribution of rain rates is well stratified by the energy.

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I. Zawadzki
and
M. De Agostinho Antonio

Abstract

Observations of raindrop size distributions in Brazil were analyzed. For long lasting records and during periods when there was no evidence of rain falling through updraft, the observations indicate that equilibrium between the coalescence and the breakup processes leads to a generic shape of the distribution such that distributions for different rain rates are proportional to each other. This is in agreement with numerical solutions to the stochastic equation. In cases where there is indication that updraft was present, the drop size distributions were markedly different. The proportionality between distributions is observed in these cases as well.

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B. J. Turner
,
I. Zawadzki
, and
U. Germann

Abstract

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.

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I. Zawadzki
,
J. Morneau
, and
R. Laprise

Abstract

Predictability, defined as the ability to forecast precipitation over an area by Lagrangian persistence, is studied for 11 radar precipitation patterns. After a time ranging between 40 and 112 min, depending on individual cases, all forecast skill is lost. Attempts at relating this range of predictability to larger-scale meteorological parameters lead to positive results when the convective available potential energy is considered alone or in combination with wind shear energy. It appears from this study that the limited range of scales properly sampled by a single radar severely hampers the possibility of establishing a solid empirical relationship between mesoscale predictability and synoptic-scale meteorological parameters.

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I. Zawadzki
,
W. Szyrmer
,
C. Bell
, and
F. Fabry

Abstract

A model of the melting snow and its radar reflectivity is presented here. The main addition to previous description of the melting layer is the explicit introduction of snow density as a variable. The model is validated with radar observations. Differences in brightband intensity for comparable precipitation rates are related here to the coexistence of supercooled cloud water (SCW) with snow above the melting level leading to riming and change in snow density. Cases where riming was suspected were selected according to the characteristics of the vertical profile of reflectivity flux above the melting layer and vertical Doppler velocities faster than expected from low-density snow. For stratiform precipitation with a melting layer, high snow-to-rain velocity ratio indicates high-density snow and consequently a small peak-to-rain reflectivity difference is expected. This relationship was computed from the model and confirmed with vertically pointing radar observations. In spite of the complexity of the physical processes present in the melting layer the model appears to capture the essential elements.

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J. Mailhot
,
J. W. Strapp
,
J. I. MacPherson
,
R. Benoit
,
S. Bélair
,
N. R. Donaldson
,
F. Froude
,
M. Benjamin
,
I. Zawadzki
, and
R. R. Rogers

The MERMOZ (Montreal-96 Experiment on Regional Mixing and Ozone) field experiment was conducted in the greater Montreal area in June 1996. The measurement program was designed to examine several aspects of boundary layer dynamics and chemical transport. The project featured high-resolution real-time simulations with a mesoscale meteorological model driving several air quality models; the deployment of a research aircraft, fully instrumented for turbulent flux measurements; and a number of other supporting meteorological measurements such as two boundary layer wind profilers, a Doppler weather radar, and a special network of surface stations, upper-air soundings, tethersondes, and ozonesondes. An overview of the MERMOZ field program is presented with some preliminary results on various aspects of the experiment.

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