Using Gap-Filling Radars in Mountainous Regions to Complement a National Radar Network: Improvements in Multiple-Doppler Wind Syntheses [Journal of Applied Meteorology and Climatology]
| By Bousquet, Olivier | |
| Proquest LLC |
ABSTRACT
The existing French Application Radar à la Météorologie Infrasynoptique (ARAMIS) operational radar network covers a vast majority of the country of
1. Introduction
Regional and national operational radar networks are a crucial component in short-term forecasting and are a key source for the detection of hazardous meteorological phenomena. In addition, their data, including radial velocity and reflectivity, are now being assimilated within high-resolution numerical models to provide additional observational information previously unavailable within the traditional, ground-based observing network (Montmerle and Faccani 2009; Caumont et al. 2010). Given their importance to weather forecasting and public safety, the ability to obtain sufficient radar coverage over large regions, mountainous terrain, and significant population centers is essential, but many times difficult to achieve.
For example, within the U.S. national Next Generation Weather Radar network (NEXRAD; Maddox et al. 2002), radars are placed approximately 200-300km apart. This spacing presents a troubling radar coverage problem, where both distance between radars and earth curvature impact the ability of the radars to scan low altitudes at far distances. These gaps in radar coverage are significant in the sense that they limit the ability to detect meteorological phenomena affecting low levels. The Collaborate Adaptive Sensing of the Atmosphere (CASA) project was created in an attempt to mitigate this problem through lower-cost X-band radars (relative to C- and S-band systems) spaced at distances of less than 30km (McLaughlin et al. 2009). An initial network of four X-band radars was set up in centralOklahoma as a test bed for this project (Philips et al. 2010), where severe thunderstorms and tornadoes frequently occur. Preliminary results show that this type of network improves low-level coverage, resolution, and detection of severe-weather events, when compared with the standard, national radar network.
On a smaller scale,
Mountains, especially those located near the sea, can facilitate the formation of extremely intense rainfall on relatively localized scales. For particularly sensitive watersheds, strong precipitation events can generate rapid and destructive floods, presenting a major threat to life and property, especially given growing urbanization and a concentration of population during the last few decades in flood-prone areas. For these reasons, the influence of mountainous topography on moist dynamics and cloud microphysics has received considerable attention in the last few years, giving rise to several field and research programs such as the Mesoscale Alpine Programme (MAP; Bougeault et al. 2001), the Improvement of Microphysical Parameterization through Observational Verification Experiment (IMPROVE; Stoelinga et al. 2003), the Intermountain Precipitation Experiment (
Focusing on the interaction of synoptic systems with the mountainous regions of
Panziera and Germann (2010) conducted an investigation of 58 orography induced precipitation events in the southern Alps. Their results show that low-level airmass instability played a role in the generation of precipitation, but to a lesser extent than the direction and speed of the onshore flow. The authors showed that the impinging wind direction impacted the location and distribution of the heaviest precipitation and that wind speed intensity played a major role in the observed precipitation rate. Results from this study indicate the kinematic parameters of the upstream airflow to be the most important factor in producing terrain-induced precipitation. Knowledge of the offshorewind flow southeast of
These findings outline the need for additional and denser three-dimensional observations within and upstream of complex terrain. Successful operation of radars within mountainous regions, such as the MeteoSwiss network (Germann et al. 2006), and small, portable X-band radars (Gabella et al. 2012) indicate the possibility to reliably collect data in these areas. Therefore, within preexisting networks, one possibility exists to implement dual-polarization, gap-filling X-band radars to fulfill the goal of enhanced data collection in previously inaccessible regions. For example, the X-NET project (Maki et al. 2010) was created to form a dense, dual-polarization, X-band radar network throughout a large portion of
A similar project, the Risques Hydrométéorologiques en Territoires de Montagnes et Mediterranéens (RHYTMME), was developed to mitigate coverage gaps in the French ARAMIS radar network and to improve the ability to forecast and study localized, high-risk precipitation events in the southern French Alps (Westrelin et al. 2012). At present, two RHYTMME radars are operational, at Mont Vial and Mont Maurel, providing coverage for themaritime FrenchAlps (Fig. 2b). Installed in 2010, the radar on Mont Vial is a Novimet, Hydrix X-band radar owned by the Centre National de la Recherche Scientifique (CNRS). The Mont Maurel radar, installed in 2011, is a Selex-Gematronik X-band radar owned and managed by Météo-
Eventually, a total of four RHYTMME, X-band, dualpolarization radars will be deployed in the Alpine region of southeast
In addition to better QPE, hydrometeor classification, and radial velocity, the availability of increased radar coverage can improve the verification of model forecast output through comparison with multiple-Doppler wind field syntheses. With the implementation of a triple-pulse repetition time (PRT) scheme (Tabary et al. 2006) for the French ARAMIS radar network, Bousquet et al. (2007, 2008b) showed thatmitigation of the ''Doppler dilemma'' allowed for long-range data collection, with a high
The use of real-time, multiple-Doppler synthesis data could provide future potential in the field of nowcasting, especially with expanded radar coverage in mountainous terrain. Extrapolation nowcasting methods, such as those used by Dixon and Wiener (1993), including forecasts of thunderstorm size, position. and intensity [or those with more advanced advection schemes, such as in Germann and Zawadzki (2002)] could be improved with the addition of wind vector synthesis data. Shortterm storm forecasting could benefit especially from wind field information surrounding and downstream of the thunderstorm. In particular, multiple-Doppler wind fields could complement existing nowcasting schemes in mountainous terrain, where persistence advection schemes may not perform as well as in open terrain. For example, analog nowcasting techniques such as those used by Panziera et al. (2011), specifically for mountainous regions, could be coupled with three-dimensional wind field data. Given the small time-scale variability that can accompany precipitation in high terrain, the addition of these data to analog techniques may prove highly beneficial.
Given the precedence for accurate multiple-Doppler retrieval within the ARAMIS network domain, data were combined from the ARAMIS and RHYTMME radar networks to compute real-time, three-dimensional, multiple-Doppler wind syntheses in regions that were previously inaccessible by the traditional S- and C-band ARAMIS radars. These syntheses reveal the advantage that gap-filling radars can provide above and upstream of mountainous terrain when combined with a preexisting traditional radar network. From these data, two case studies were selected and further analyzed to illustrate how these gap-filling radars can improve the understanding of onshore flow in extreme southeastern
2. Methodology
The radars in the ARAMIS network collect radial velocity, reflectivity, and (depending on the radar) a suite of dual-polarimetric variables every 15min at elevations ranging from 0.58 to 608. A triple-PRT scheme is used (Tabary et al. 2006) allowing for an unambiguousNyquist velocity of 60ms21. Dual-polarimetric variables are collected and used in a fuzzy logic algorithm (Gourley et al. 2007) to separate nonprecipitating from precipitating echoes. This information is then used to filter the radar data of ground clutter, second trip, and other anomalous returns, in order to prepare the data for multiple-Doppler retrieval. The reader is referred to Bousquet et al. (2008a,b) for more details about ARAMIS radar data preprocessing.
The processing algorithm used by the ARAMIS radar network was adapted to the RHYTMME X-band radars, and successfully implemented to allow for automated editing and filtering of erroneous and other anomalous radar data. Specifically, the dual-polarimetric variables are collected, followed by an attenuation correction for horizontal and differential reflectivity, given that the RHYTMME radars operate at X band. Conducted on a gate-to-gate basis for both horizontal reflectivity ZH and differential reflectivity ZDP, the attenuation correction consists of a proportionality constant (for X band, gH 5 0.28 and gDP 5 0.04) multiplied by the differential phase FDP. This sum is then added to the respective reflectivities. After attenuation correction, the signal-to-noise ratio (SNR) is calculated and echo type is differentiated using the fuzzy logic algorithm with probability density function (PDF) curves for precipitating and specific, nonprecipitating (insects, birds, ground) echoes. This algorithm utilizes horizontal reflectivityZH, the correlation coefficient rHV, the spectrum width sy, the SNR, the texture of the differential reflectivity ZDR, and knowledge of the melting-layer height (derived from both radar and model data) with the PDF curves to determine echo type (Al-Sakka et al. 2012).
However, noise and other errors are produced by the dual-PRF scheme used by Mont Vial and the triple-PRT scheme used by Mont Maurel, in part due to small ratios between PRF values (e.g., Jorgensen et al. 2000; Augros and Tabary 2009), and require amedian filter and further editing to ensure that the data are error free. Application of median filters to remove erroneous radial velocity data from radars using dual-PRF and triple-PRT schemes has been successfully implemented in the past (Tabary et al. 2006; Bousquet el al. 2008b; Montmerle and Faccani 2009). It is this combination of dual-polarimetric hydrometeor classification and median filter editing that allows for realtime dual- and multiple-Doppler synthesis retrieval.
The scanning strategies of the Mont Vial and Mont Maurel radars used in the multiple-Doppler syntheses are shown in Tables 1 and 2, respectively, indicating the dual-PRF and triple-PRT schemes used. Mont Vial records dual-PRF volume scans every 15 min, whereas Mont Maurel completes volume scans every 5 min, allowing for accurate time calibration of the datasets with the ARAMIS radars for multiple-Doppler syntheses.
The Mont Vial radar is located approximately 20km north of the city of
Prior to any multiple-Doppler retrievals, fixed-height coverage maps were generated to show the potential multiple-Doppler retrieval region with and without Mont Vial and Mont Maurel at specific vertical levels. At 2.5km MSL, the fixed-height coverage for the three ARAMIS radars is shown (Fig. 3a). Dual- and multiple- Doppler coverage is already extensive over a large portion of the domain. However, with the addition of Mont Vial (Fig. 3b) andMontMaurel (Fig. 3c), the coverage at 2.5 kmMSL is expanded with dual- andmultiple-Doppler coverage extending well into the
To conduct the multiple-Doppler syntheses, unfolded, edited radial velocity data were first converted frompolar to Cartesian coordinates using a Cressman interpolation scheme (Cressman 1959), after which the radial velocities existing at each available grid point were used to generate horizontal and vertical wind components. The process of data interpolation and wind synthesis was carried out using the multiple-Doppler synthesis and continuity adjustment technique (MUSCAT) software suite (Bousquet and Chong 1998). Specifically, MUSCAT was used to retrieve three-dimensional wind vectors at intervals of 1 km horizontally and 500m vertically. The radius of influence used in the Cartesian interpolation was 2 kmin the horizontal and 1 km in the vertical.
The two events chosen for analysis provide evidence of important additional coverage from the RHYTMME radars, and illustrate contrasting low-level wind regimes, allowing for a unique opportunity to assess onshore flow. The first case occurred prior to Mont Maurel data availability, between the evening of
The second precipitation event chosen for analysis occurred on
3. Analysis
a. Coverage
A quantitative assessment was first conducted to calculate the added coverage the RHYTMME radars provide. Increases in coverage were computed for the total volumetric area scanned by the radars (up to 12 km MSL), delineating between single- and multiple-Doppler coverage. When adding Mont Vial and Mont Maurel to the ARAMIS network, single-Doppler volumetric coverage increases by 8% (122 086 km2) within the domain specified in Fig. 3. Because of a large maximum unambiguous range incorporated by the S- and C-band ARAMIS radars, this increase in coverage generally occurs at low levels over high terrain near the RHYTMME radars, a valuable region for additional total volumetric coverage in the domain.
However, a major increase is shown when assessing the increase in multiple-Doppler coverage. Dual- and overdetermined-Doppler coverage increases by 34% (318 166km2), representing an additional one-third of the three-dimensional domain specified. It is this latter increase in multiple-Doppler coverage that allows for wind-flow retrieval over a much broader region, as well as an improvement in the accuracy and resolution of these analyses due to the combination of the ARAMIS network with the additional RHYTMME radars.
b. Mesoscale environments and radar observations for
Precipitation associated with the synoptic system of
At 3 km MSL (Fig. 6), wind vectors offthe coast of
Given the strong precipitation created during this event, Fig. 6 shows the importance that the Mont Vial radar has for estimating the strength of precipitation over southeast
In addition to improved reflectivity measurements, the RHYTMME radars can help resolve low-level wind flow within southeast
The second precipitation event of
c. Orographic precipitation implications
Orographic precipitation stability metrics presented previously in the literature (discussed above) were used to assess the nature of the wind flow for both case studies near mountainous terrain. Improved and expanded wind fields retrieved from a combination of the ARAMIS and RHYTMME networks allowed for interpretation of these results adjacent to orography in regions previously inaccessible by the ARAMIS network.
For the
Vertical profiles of low-level temperature and mixing ratio from
The uniform southerly flow over varying terrain indicates that air is able to traverse the mountainous regions of southern
When analyzing the
The resulting convergence identified in the multiple- Doppler syntheses, collocated with the blocked flow, corresponds well with regions of high reflectivity, particularly south of the
d. Independent RHYTMME dual-Doppler analysis
A final analysis was conducted to assess the multiple- Doppler data quality of the two RHYTMME radars, independent of the ARAMIS network. Figure 9 shows dual-Doppler wind field retrievals between the two X-band radars, Mont Vial and Mont Maurel, for
4. Conclusions
The current French ARAMIS radar network lacks sufficient coverage in the high-terrain regions of southeast
This study illustrates the invaluable addition that the gap-filling Mont Vial and Mont Maurel radars provide. To exemplify these advantages, results are presented from multiple-Doppler syntheses from
Further analysis of the
The use of multiple-Doppler wind field data in numerical simulations represents a promising area of future research. Data from real-time, multiple-Doppler wind syntheses can be incorporated into model forecasts at initialization to assess the potential benefit they may provide. Specifically, data can be incorporated into research-based models, such as the Applications de la Recherche à Mésoéchelle model (AROME; Seity et al. 2011), to assess potential improvements in forecasting accuracy of rainfall amount and location, wind speed and direction, and the overall timing of high-precipitation events.
Acknowledgments. The authors thank the
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JEFFREY BECK AND OLIVIER BOUSQUET
Météo-
(Manuscript received
Corresponding author address:
E-mail: [email protected]
| Copyright: | (c) 2013 American Meteorological Society |
| Wordcount: | 6604 |



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