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Urs Germann and Jürg Joss

Abstract

In the Alps, the volume visible by a radar is reduced because of ground clutter, elevated horizon, and earth curvature. This often inhibits a direct view on precipitation close to the ground. When using radar measurements from aloft to estimate precipitation rates at ground level, the measurements must be corrected for the vertical change of the radar echo (the profile) caused by the growth and transformation of precipitation. In this paper a robust profile-correction scheme for operational use in complex orography is presented. The aim is to correct for the large errors related to the profile in an Alpine environment: frequent underestimation caused by the vertical decrease of the radar echo, and occasional overestimation in the bright band. The profile is determined from volumetric radar data integrated over a few hours within a 70-km range of the radar (mesobeta scale). The correction scheme is verified by comparing radar estimates to gauge measurements of 247 h of summer and winter precipitation in a highly mountainous area. During the selected period, 10 gauges collected a total of 3966 mm of water. Four concepts to estimate ground-level precipitation are compared: the vertical maximum echo, the lowest visible echo, estimates corrected with the average-event profile, and estimates corrected using the mesobeta profile. Comparisons with the ground truth show that in summer profile correction considerably reduces the bias and scatter. The root-mean-square error diminishes by a factor of 2. Thus, corrected radar images give a much better overall view of the precipitation field than uncorrected ones. In winter, the improvement is found in a very significant reduction of the bias. The algorithm is currently being implemented in the operational radar network of MeteoSwiss. Long-term verification is needed after a few years of operation.

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Urs Germann and Isztar Zawadzki

Abstract

Eulerian and Lagrangian persistence of precipitation patterns derived from continental-scale radar composite images are used as a measure of predictability and for nowcasting [the McGill algorithm for precipitation nowcasting by Lagrangian extrapolation (MAPLE)]. A previous paper introduced the method and focused on the lifetime of patterns of rainfall rates and the scale dependence of predictability. This paper shows how the method of persistence of radar precipitation patterns can be extended to produce probabilistic forecasts. For many applications, probabilistic information is at least as important as the expected point value. Four techniques are presented and compared. One is entirely new and makes use of the intrinsic relationship between scale and predictability. The results with this technique suggest potential use for downscaling of numerical model output. For the 143 h of precipitation analyzed so far, roughly a factor of 2 was obtained between lead times of Eulerian and Lagrangian techniques. Three of the four techniques involve a scale parameter. The slope of the relationship between optimum scale and lead time is about 1 and 2 km min−1 for Lagrangian and Eulerian techniques, respectively. The skill scores obtained for the four techniques can be used as a measure of predictability in terms of probabilistic rainfall rates. The progress of other probabilistic forecasting methods, such as expert systems or numerical models, can be evaluated against the standard set by simple persistence.

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Urs Germann and Jürg Joss

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The authors use variograms of radar reflectivity as a summary statistic to describe the spatial continuity of Alpine precipitation on mesogamma scales. First, how to obtain such variograms is discussed. Second, a set of typical variograms of Alpine precipitation is found. Third, some examples are given on how these variograms can be used to tackle several questions such as, What spatial variation of precipitation rate can be found in Alpine catchments? What difference can be expected between the measurements at two points separated by a given distance? To what accuracy can areal precipitation be estimated from point observations? Are there preferred regions for convection in Alpine precipitation? Variograms are obtained using a method-of-moments estimator together with high-resolution polar reflectivity data of well-visible regions. Depending on the application, the variogram was determined in terms of linear precipitation rate, logarithmic reflectivity, or linear reflectivity. Spatial continuity was found to vary significantly both in time and space in the various types of Alpine precipitation analyzed so far. At a separation distance of 10 km, the expected difference of reflectivity ranges from 4 dBZ (factor of 2.5 in stratiform rain or snow) to about 13 dBZ (factor of 20 in a mesoscale convective system). In a 96-h period of heavy rain in the southern European Alps, maximum variation occurred in upslope regions (frequent convection), while close to the crest of the Alps the variation was relatively weak (persistent stratiform rain). The representativeness of a point observation, which can be quantified given the variogram, therefore depends on both the time and the location within the Alps and also on the integration time (integrated rainfall maps being less variable than instantaneous ones). For a 576-km2 basin and 40-min average rain, the fractional error of the basin precipitation estimated by a gauge measurement ranges from 11% (variogram of stratiform autumn rain) to 65% (variogram of a mesoscale convective system). Next steps will extend the variogram analyses to a larger space–time domain toward a climatic description of spatial continuity of Alpine precipitation.

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Urs Germann and Isztar Zawadzki

Abstract

The lifetime of precipitation patterns in Eulerian and Lagrangian space derived from continental-scale radar images is used as a measure of predictability. A three-step procedure is proposed. First, the motion field of precipitation is determined by variational radar echo tracking. Second, radar reflectivity is advected by means of a modified semi-Lagrangian advection scheme assuming stationary motion. Third, the Eulerian and Lagrangian persistence forecasts are compared to observations to calculate the lifetime and other measures of predictability. The procedure is repeated with images that have been decomposed according to scales to describe the scale-dependence of predictability.

The analysis has a threefold application: (i) determine the scale-dependence of predictability, (ii) set a standard against which the skill for quantitative precipitation forecasting by numerical modeling can be evaluated, and (iii) extend nowcasting by optimal extrapolation of radar precipitation patterns. The methodology can be applied to other field variables such as brightness temperatures of weather satellites imagery.

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Pierre Tabary, Georges Scialom, and Urs Germann

Abstract

Doppler radar measurements provide the radial wind within an unambiguous interval due to the limited value of the sampling frequency (pulse repetition frequency). Many algorithms have been developed to retrieve true wind velocities from measured aliased wind velocities. However, these algorithms are time consuming, which can be a constraint in an operational context. Besides, most of them need independent information on the wind generally provided by complementary neighbor measurements such as radiosonde or wind profiler. This paper describes a new method aimed at providing an estimate of the real wind directly from aliased wind measurements without prior dealiasing, allowing the method to be used in real time by operational radars without additional information from other instruments. A potential application of the method is to provide a reference wind profile that can be used, in a second step, to dealias radial velocities.

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Katja Friedrich, Urs Germann, and Pierre Tabary

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The influence of ground clutter contamination on the estimation of polarimetric radar parameters, horizontal reflectivity (Zh), differential reflectivity (Z dr), correlation coefficient (ρ hυ), and differential propagation phase (ϕ dp) was examined. This study aims to derive the critical level of ground clutter contamination for Zh, Z dr, ρ hυ, and ϕ dp at which ground clutter influence exceeds predefined precision thresholds. Reference data with minimal ground clutter contamination consist of eight precipitation fields measured during three rain events characterized by stratiform and convective precipitation. Data were collected at an elevation angle of 0.8° by the Météo-France operational, polarimetric Doppler C-band weather radar located in Trappes, France, ∼30 km southwest of Paris. Nine different ground clutter signatures, ranging from point targets to more complex signatures typical for mountain ranges or urban obstacles, were added to the precipitation fields. This is done at the level of raw in-phase and quadrature component data in the two polarimetric channels. For each ground clutter signature, 30 simulations were conducted in which the mean reflectivity of ground clutter within the resolution volume varied between being 30 dB higher to 30 dB lower than the mean reflectivity of precipitation. Differences in Zh, Z dr, ρυ, and ϕ dp between simulation and reference were shown as a function of ratio between ground clutter and precipitation intensities.

As a result of this study, horizontal reflectivity showed the lowest sensitivity to ground clutter contamination. Furthermore, a precision of 1.7 dBZ in Zh is achieved on average when the precipitation and ground clutter intensities are equal. Requiring a precision of 0.2 dB in Z dr and 3° in ϕ dp, the reflectivity of precipitation needs to be on average ∼5.5 and ∼6 dB, respectively, higher compared to the reflectivity of ground clutter. The analysis also indicates that the highest sensitivity to the nine clutter signatures was derived for ρ hυ. To meet a predefined precision threshold of 0.02, reflectivity of precipitation needs to be ∼13.5 dB higher than the reflectivity of ground clutter.

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James V. Rudolph, Katja Friedrich, and Urs Germann

Abstract

Projections of twenty-first-century precipitation for seven Swiss river basins are generated by linking high-resolution (2 km × 2 km) radar-estimated precipitation observations to a global climate model (GCM) via synoptic weather patterns. The use of synoptic patterns characterizes the effect of changes in large-scale circulation, or dynamic effects, on precipitation. In each basin observed total daily precipitation received during advective synoptic patterns is shown to be dependent on the basin’s general topographic aspect. Across all basins convective synoptic patterns follow the same trend in total daily precipitation with cyclonic patterns consistently producing a larger amount of precipitation than anticyclonic patterns. Identification of synoptic patterns from a GCM for the twenty-first century [Community Climate System Model, version 3.0, (CCSM3)] shows increasing frequency of anticyclonic synoptic patterns, decreasing frequency of cyclonic patterns, and constant frequency of advective patterns over Switzerland. When coupled with observed radar-estimated precipitation for each synoptic pattern, the changes in synoptic pattern frequencies result in an approximately 10%–15% decrease in decadal precipitation over the course of the twenty-first century for seven Swiss river basins. The study results also show an insignificant change in the future (twenty-first century) probability of exceeding the current (2000–08) 95th quantile of total precipitation. The lack of a trend in exceeding the 95th quantile of precipitation in combination with a decreasing trend in total precipitation provides evidence that dynamic effects will not result in increased frequency of heavy precipitation events, but that heavy precipitation will account for a greater proportion of total precipitation in Swiss river basins by the end of the twenty-first century.

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Urs Germann, Isztar Zawadzki, and Barry Turner

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Predictability of precipitation is examined from storm to synoptic scales through an experimental approach using continent-scale radar composite images. The lifetime of radar reflectivity patterns in Eulerian and Lagrangian coordinates is taken as a measure of predictability. The results are stratified according to scale, location, and time in order to determine how predictability depends on these parameters. Three companion papers give a detailed description of the methodology, and present results are obtained for 143 hours of North American warm season rainfall with emphasis on lifetime, scale dependence, optimum smoothing of forecast fields, and predictability in terms of probabilistic rainfall rates.

This paper discusses the sources of forecast uncertainty and extends the analysis to a total of 1424 hours of rainfall. In a Lagrangian persistence framework the predictability problem can be separated into a component associated with growth of precipitation and a component associated with changes in the storm motion field. The role of changes in the motion field turned out to be small but not negligible. A stratification of lifetime according to location reveals the regions with high predictability and significant nonstationary storm motion.

This work is of high practical significance for three reasons: First, Lagrangian persistence of radar patterns was proved to have skill for probabilistic precipitation nowcasting. The discussion of the sources of uncertainty provides a guideline for further improvements. Second, a scale- and location-dependent benchmark is obtained against which the progress of other precipitation forecasting techniques can be evaluated. And, third, the experimental approach to predictability presented in this paper is a valuable contribution to the fundamental question of predictability of precipitation.

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James V. Rudolph, Katja Friedrich, and Urs Germann

Abstract

A 9-yr (2000–08) analysis of precipitation characteristics for the central and western European Alps has been generated from ground-based operational weather radar data provided by the Swiss radar network. The radar-based precipitation analysis focuses on the relationship between synoptic-scale weather patterns and mesoscale precipitation distribution over complex alpine terrain. The analysis divides the Alps into six regions (each approximately 200 × 200 km2 in size)—one on the northern side, two each on the western and southern sides of the Alps, and one in the Massif Central—representing various orographic aspects and localized climates within the radar coverage area. For each region, estimated precipitation rate derived from radar data is analyzed on a seasonal basis for total daily precipitation and frequency of high-precipitation-rate events. The summer season has the highest total daily precipitation for all regions in the study, whereas median values of daily precipitation in winter are less than one-half of median daily precipitation for summer. For all regions, high-precipitation-rate events occur most frequently in the summer. Daily synoptic-scale weather patterns are associated with total daily precipitation and frequency of high precipitation rate to show that an advective synoptic-scale pattern with southerly midtropospheric flow results in the highest median and 90th-quantile values for total daily precipitation and that a convective synoptic-scale pattern results in elevated frequency of extreme-precipitation-rate events.

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Katja Friedrich, Urs Germann, Jonathan J. Gourley, and Pierre Tabary

Abstract

Radar reflectivity (Z h), differential reflectivity (Z dr), and specific differential phase (K dp) measured from the operational, polarimetric weather radar located in Trappes, France, were used to examine the effects of radar beam shielding on rainfall estimation. The objective of this study is to investigate the degree of immunity of K dp-based rainfall estimates to beam shielding for C-band radar data during four typical rain events encountered in Europe. The rain events include two cold frontal rainbands with average rainfall rates of 7 and 17 mm h−1, respectively, and two summertime convective rain events with average rainfall rates of 11 and 22 mm h−1.

The large effects of beam shielding on rainfall accumulation were observed for algorithms using Z h and Z dr with differences of up to ∼2 dB (40%) compared to a K dp-based algorithm over a power loss range of 0–8 dB. This analysis reveals that Z dr and K dp are not affected by partial beam shielding. Standard reflectivity corrections based on the degree of beam shielding would have overestimated rainfall rates by up to 1.5 dB for less than 40% beam shielding and up to 3 dB for beam shielding less than 75%. The investigation also examined the sensitivity of beam shielding effects on rainfall rate estimation to (i) axis–ratio parameterization and drop size distribution, (ii) methods used to smooth profiles of differential propagation phase (ϕ dp) and estimate K dp, and (iii) event-to-event variability. Although rainfall estimates were sensitive to drop size distribution and axis–ratio parameterization, differences between Z h- and K dp-based rainfall rates increased independently from those parameters with amount of shielding. Different approaches to smoothing ϕ dp profiles and estimating K dp were examined and showed little impact on results.

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