Corrections of Precipitation Particle Size Distribution Measured by a Parsivel OTT2 Disdrometer under Windy Conditions in the Antisana Massif, Ecuador

Abstract

Monitoring precipitation in mountainous areas using traditional tipping-bucket rain gauges (TPB) has become challenging in sites with strong variations of air temperature and wind speed (Ws). The drop size distributions (DSD), amount, and precipitation-type of a Parsivel OTT2 disdrometer installed at 4730 m above sea level (close to the 0 °C isotherm) in the glacier foreland of the Antisana volcano in Ecuador are used to analyze the precipitation type. To correct the DSDs, we removed spurious particles and shifted fall velocities such that the mean value matches with the fall velocity–diameter relationship of rain, snow, graupel, and hail. Solid (SP) and liquid precipitation (LP) were identified through −1 and 3 °C thresholds and then grouped into low, medium, and high Ws categories by k-means approach. Changes in DSDs were tracked using concentration spectra and particle’s contribution by diameter and fall velocity. Thus, variations of concentration/dispersion and removed hydrometeors were linked with Ws changes. Corrected precipitation, assuming constant density (1 g cm−3), gives reliable results for LP with respect to measurements at TPB and overestimates SP measured in disdrometer. Therefore, corrected precipitation varying density models achieved fewer differences. These results are the first insight toward the understating of precipitation microphysics in a high-altitude site of the tropical Andes.

Parsimonious Models of Precipitation Phase Derived from Random Forest Knowledge: Intercomparing Logistic Models, Neural Networks, and Random Forest Models

“…Furthermore, changes in temperature and atmosphere's saturation can also alter the precipitation phase due to pressure changes driven by changes in vertical air velocity or vertical air movement [48]. The PRAA station fulfills all these conditions due to (1) its altitude near the 0 • C isotherm located between 4800-5100 m.a.s.l [49]; (2) large variability of temperature and specific humidity between days; and (3) strong wind speed around 4.6 m/s with gusts up to 12 m/s [29]. Therefore, models based on both temperature and humidity variables achieved better results to forecast PP, as occurred with LM1 and LM5.…”

“…The disdrometer is located at 4730 m.a.s.l in the glacier foreland of the Antisana volcano. The disdrometer measured data were corrected [25][26][27][28][29], for diameter, speed, and bulk variables. However, the PP recorded by the disdrometer was considered adequate.…”

“…This could be related to differences in climatic conditions between inner tropics and the Alps. On the other hand, we computed the rain fraction with P50 calibrated values for LM1 (Table 5) and the mean temperature (2.1 • C) and the relative humidity (81%) of the site (according [29]). Afterwards, it was compared with the rain fraction computed with the mean temperature and the relationship derived by [17] for the Antisana.…”

Performance of precipitation phase partitioning methods and their impact on snowpack evolution in a humid continental climate

“…Finally, the precipitation phase was determined from the 1-min WaWa weather codes provided by the disdrometer using the classification method from Gualco et al (2021). These codes represent the type of precipitation (e.g., drizzle, rain, snow, or hail) determined internally by the disdrometer.…”

Zależności Z-R dla różnych typów opadów jako narzędzie do radarowego szacowania wielkości opadów = The Z-R relationships for different types of precipitation as a tool for radar-based precipitation estimation

“…Znacznie więcej badań z wykorzystaniem różnego typu disdrometrów prowadzi się poza krajem. Część z nich jest realizowana przy zastosowaniu disdrometrów laserowych Parsivel (Krajewski et al, 2006;Jaffrain i Berne, 2011;Thurai et al, 2011;Tokay et al, 2013;Jwa et al, 2020;Gualco et al, 2021). Zakres tych badań obejmuje zagadnienia niepewności i błędu pomiarów przy zastosowaniu tego typu instrumentów, rozpoznania rozkładów wielkości kropel w czasie zdarzeń, a także dotyczące zastosowań aplikacyjnych disdrometrów.…”