Multi-sensor observations of an elevated rotor during a mountain wave event in the Eastern Pyrenees

Udina, Mireia; Bech, Joan; González, Sergi; Soler, M. R.; Paci, Alexandre; Miró, Josep Ramon; Trapero, Laura; Donier, Jean Marie; Douffet, Thierry; Codina, Bernat; Pineda, Nicolau

doi:10.1016/j.atmosres.2019.104698

Cited by 13 publications

(9 citation statements)

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“…The location is a relatively wide valley oriented west to east, with limited radar coverage due to orographic beam blockage (Bech et al [40], Trapero et al [41]) so most of the MRR beam cannot be directly compared with existing ground-based weather radar observations. The Cerdanya-2017 field campaign aimed at studying various complex terrain phenomena, including cold pool formation, mountain waves and orographic precipitation-see Gonzalez et al [17]; Udina et al [42] for more details.…”

Section: Instruments and Site Descriptionmentioning

confidence: 99%

Precipitation Type Classification of Micro Rain Radar Data Using an Improved Doppler Spectral Processing Methodology

et al. 2020

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This paper describes a methodology for processing spectral raw data from Micro Rain Radar (MRR), a K-band vertically pointing Doppler radar designed to observe precipitation profiles. The objective is to provide a set of radar integral parameters and derived variables, including a precipitation type classification. The methodology first includes an improved noise level determination, peak signal detection and Doppler dealiasing, allowing us to consider the upward movements of precipitation particles. A second step computes for each of the height bin radar moments, such as equivalent reflectivity (Ze), average Doppler vertical speed (W), spectral width (σ), the skewness and kurtosis. A third step performs a precipitation type classification for each bin height, considering snow, drizzle, rain, hail, and mixed (rain and snow or graupel). For liquid precipitation types, additional variables are computed, such as liquid water content (LWC), rain rate (RR), or gamma distribution parameters, such as the liquid water content normalized intercept (Nw) or the mean mass-weighted raindrop diameter (Dm) to classify stratiform or convective rainfall regimes. The methodology is applied to data recorded at the Eastern Pyrenees mountains (NE Spain), first with a detailed case study where results are compared with different instruments and, finally, with a 32-day analysis where the hydrometeor classification is compared with co-located Parsivel disdrometer precipitation-type present weather observations. The hydrometeor classification is evaluated with contingency table scores, including Probability of Detection (POD), False Alarm Rate (FAR), and Odds Ratio Skill Score (ORSS). The results indicate a very good capacity of Method3 to distinguish rainfall and snow (PODs equal or greater than 0.97), satisfactory results for mixed and drizzle (PODs of 0.79 and 0.69) and acceptable for a reduced number of hail cases (0.55), with relatively low rate of false alarms and good skill compared to random chance in all cases (FAR < 0.30, ORSS > 0.70). The methodology is available as a Python language program called RaProM at the public github repository.

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Section: Instruments and Site Descriptionmentioning

confidence: 99%

Precipitation Type Classification of Micro Rain Radar Data Using an Improved Doppler Spectral Processing Methodology

et al. 2020

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“…Extreme minimum absolute temperatures occur during winter, leading to strong cold-air pools 20 . Precipitation events occur both in warm and cold seasons, some of them associated with meridional synoptic flows impinging perpendicularly to the mountain ranges 21 – 23 .…”

Section: Introductionmentioning

confidence: 99%

Monitoring storm evolution using a high-density seismic network

Díaz¹,

Ruiz²,

Udina

et al. 2023

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Data acquired by a dense seismic network deployed in the Cerdanya basin (Eastern Pyrenees) is used to track the temporal and spatial evolution of meteorological events such as rainfall episodes or thunderstorms. Comparing seismic and meteorological data, we show that for frequencies above 40 Hz, the dominant source of seismic noise is rainfall and hence the amplitude of the seismic data can be used as a proxy of rainfall. The interstation distance of 1.5 km provides an unprecedented spatial resolution of the evolution of rainfall episodes along the basin. Two specific episodes, one dominated by stratiform rain and the second one dominated by convective rain, are analyzed in detail, using high resolution disdrometer data from a meteorological site near one of the seismic instruments. Seismic amplitude variations follow a similar evolution to radar reflectivity values, but in some stratiform precipitation cases, it differs from the radar-derived precipitation estimates in this region of abrupt topography, where radar may suffer antenna beam blockage. Hence, we demonstrate the added value of seismic data to complement other sources of information such as rain-gauge or weather radar observations to describe the evolution of ground-level rainfall fields at high spatial and temporal resolution. The seismic power and the rainfall intensity have an exponential relationship and the periods with larger seismic power are coincident. The time intervals with rain drops diameters exceeding 3.5 mm do not result in increased seismic amplitudes, suggesting that there is a threshold value from which seismic data are no longer proportional to the size of the drops. Thunderstorms can be identified by the recording of the sonic waves generated by thunders, with. Single thunders detected to distances of a few tens of kilometers. As the propagation of these acoustic waves is expected to be strongly affected by parameters as air humidity, temperature variations or wind, the seismic data could provide an excellent tool to investigate atmospheric properties variations during thunderstorms.

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“…They often produce violent downdrafts on the immediate leeward side of the mountain barrier (Federal Aviation Administration, 2016). Also, these horizontal propagating waves generate rotors very close to the surface, as well as vertical windshear, being extremely dangerous in terms of aviation safety (Klemp and Lilly, 1975;Doyle and Durran, 2002;Sharman et al, 2012;Udina et al, 2020) Vertical propagating waves are tied to a different form of turbulence due to the breaking of the waves. This occurs in the middle levels of the atmosphere, and they are dangerous for aviation as well (Kim and Chun, 2011;Lilly, 1978).…”

Section: Introductionmentioning

confidence: 99%