Precipitation type classification of micro rain radar data using an improved doppler spectral processing methodology

This research was funded by the Spanish Government through projects CGL2015-65627-C3-1-R, CGL2015-65627-C3-2-R (MINECO/FEDER), CGL2016-81828-REDT and RTI2018-098693-B-C32 (AEI/FEDER).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 0.70). The methodology is available as a Python language program called RaProM at the public github repository

A new methodology to characterise the radar bright band using doppler spectral moments from vertically pointing radar observations

The detection and characterisation of the radar Bright Band (BB) are essential for many applications of weather radar quantitative precipitation estimates, such as heavy rainfall surveillance, hydrological modelling or numerical weather prediction data assimilation. This study presents a new technique to detect the radar BB levels (top, peak and bottom) for Doppler radar spectral moments from the vertically pointing radars applied here to a K-band radar, the MRR-Pro (Micro Rain Radar). The methodology includes signal and noise detection and dealiasing schemes to provide realistic vertical Doppler velocities of precipitating hydrometeors, subsequent calculation of Doppler moments and associated parameters and BB detection and characterisation. Retrieved BB properties are compared with the melting level provided by the MRR-Pro manufacturer software and also with the 0 °C levels for both dry-bulb temperature (freezing level) and wet-bulb temperature from co-located radio soundings in 39 days. In addition, a co-located Parsivel disdrometer is used to analyse the equivalent reflectivity of the lowest radar height bins confirming consistent results of the new signal and noise detection scheme. The processing methodology is coded in a Python program called RaProM-Pro which is freely available in the GitHub repository.This research was partly funded by the project “Analysis of Precipitation Processes in the Eastern Ebro Subbasin” (WISE-PreP, RTI2018-098693-B-C32, MINECO/FEDER) and theWater Research Institute (IdRA) of the University of Barcelona

Flower-mediated plant-butterfly interactions in an heterogeneous tropical coastal ecosystem

Background Interspecific interactions play an important role in determining species richness and persistence in a given locality. However at some sites, the studies, especially for interaction networks on adult butterflies are scarce. The present study aimed the following objectives: (1) determine butterfly species richness and diversity that visit flowering plants, (2) compare species richness and diversity in butterfly-plant interactions among six different vegetation types and (3) analyze the structure of butterfly-flowering plant interaction networks mediated by flowers. Methods The study was developed in six vegetation types within the natural reserve of La Mancha, located in Veracruz, Mexico. In each vegetation type, we recorded the frequency of flower visits by butterflies monthly in round plots (of radius 5 m) for 12 months. We calculated Shannon diversity for butterfly species and diversity of interactions per vegetation type. We determined the classic Jaccard similarity index among vegetation types and estimated parameters at network and species-level. Results We found 123 species of butterflies belonging to 11 families and 87 genera. The highest number of species belonged to Hesperiidae (46 species), followed by Nymphalidae (28) and Pieridae (14). The highest butterfly diversity and interaction diversity was observed in pioneer dune vegetation (PDV), coastal dune scrub (CDS) and tropical deciduous flooding forest and wetland (TDF-W). The same order of vegetation types was found for interaction diversity. Highest species similarity was found between PDV-CDS and PDV-TDF. The butterfly-plant interaction network showed a nested structure with one module. The species Ascia monuste, Euptoieta hegesia and Leptotes cassius were the most generalist in the network, while Horama oedippus, E. hegesia, and L. cassius were the species with highest dependencies per plant species. Discussion Our study is important because it constitutes a pioneer study of butterfly-plant interactions in this protected area, at least for adult butterflies; it shows the diversity of interactions among flowering plants and butterflies. Our research constitutes the first approach (at a community level) to explore the functional role of pollination services that butterflies provide to plant communities. We highlighted that open areas show a higher diversity and these areas shared a higher number of species that shaded sites. In the interaction networks parameters, our results highlighted the higher dependence of butterflies by the flowers on which they feed than vice versa. In conclusion, the plant species (as a feeding resource) seem to limit the presence of butterfly species. Thus, this protected area is highly relevant for Lepidoptera diversity and the interaction between these insects and flowering plants. We suggest that studying plant and butterfly diversity in tropical habitats will provide insight into their interspecific interactions and community structure