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

Drop size distribution variability in central argentina during relampago-cacti

The Remote sensing of Electrification, Lightning, And Meso-scale/micro-scale Processes with Adaptive Ground Observations (RELAMPAGO) and the Cloud, Aerosol, and Complex Terrain Interactions Experiment Proposal (CACTI) field campaigns provided an unprecedented thirteendisdrometer dataset in Central Argentina during the Intensive (IOP, 15 November to 15 December 2018) and Extended (EOP, 15 October 2018 to 30 April 2019) Observational Periods. The drop size distribution (DSD) parameters and their variability were analyzed across the region of interest, which was divided into three subregions characterized by the differing proximity to the Sierras de Córdoba (SDC), in order to assess the impact of complex terrain on the DSD parameters. A rigorous quality control of the data was first performed. The frequency distributions of DSD-derived parameters were analyzed, including the normalized intercept parameter (logNw), the mean volume diameter (D0), the mean mass diameter (Dm), the shape parameter (µ), the liquid water content (LWC), and the rain rate (R). The region closest to the SDC presented higher values of logNw, lower D0, and higher µ, while the opposite occurred in the farthest region, i.e., the concentration of small drops decreased while the concentration of bigger drops increased with the distance to the east of the SDC. Furthermore, the region closest to the SDC showed a bimodal distribution of D0: the lower values of D0 were associated with higher values of logNw and were found more frequently during the afternoon, while the higher D0 were associated with lower logNw and occurred more frequently during the night. The data were analyzed in comparison to the statistical analysis of Dolan et al. 2018 and sorted according to the classification proposed in the cited study. The logNw-D0 and LWC-D0 two-dimensional distributions allowed further discussion around the applicability of other mid-latitude and global precipitation classification schemes (startiform/convection) in the region of interest. Finally, three precipitation case studies were analyzed with supporting polarimetric radar data in order to relate the DSD characteristics to the precipitation type and the microphysical processes involved in each case.Fil: Casanovas, Candela Rocío. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Instituto Franco-Argentino sobre Estudios del Clima y sus Impactos; ArgentinaFil: Salio, Paola Veronica. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Instituto Franco-Argentino sobre Estudios del Clima y sus Impactos; ArgentinaFil: Galligani, Victoria Sol. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Instituto Franco-Argentino sobre Estudios del Clima y sus Impactos; ArgentinaFil: Dolan, Brenda. State University of Colorado - Fort Collins; Estados UnidosFil: Nesbitt, Stephen William. University of Illinois at Urbana; Estados Unido

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

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

Satellite and Radar Remote Sensing of Tropical Cyclones to Quantify Microphysical and Precipitation Processes

Precipitation microphysics in tropical cyclones (TCs) are often poorly represented in numerical simulations, which ultimately affects TC structure, evolution, and prediction. This provides a large incentive to better observe and understand the underlying microphysical processes in TCs in order to improve precipitation forecasts and improve warning operations. Recently, ground-based polarimetric radar observations have been able to capture the evolution and structure of precipitation in landfalling TCs in the United States, revealing numerous microphysical processes through the investigation of vertical profiles of dual-polarization radar variables. While ground radars are a useful tool for quantifying precipitation processes in TCs, they are unable to sample precipitation when TCs are over the open ocean. Therefore when ground radar networks are sparse or non-existent, space-borne radar can provide precipitation retrievals of TCs at snapshots in time. This is particularly useful for monitoring the evolution of precipitation in TCs prior to landfall. Specifically, this dissertation investigates precipitation microphysics in TCs using the NASA Global Precipitation Measurement (GPM) mission dual-frequency precipitation radar (DPR) on a global scale, and is complimented by polarimetric ground radar observations, disdrometer data, and reanalysis data when available

Processament de perfils de precipitació obtinguts amb radar Doppler

[cat] En la actualitat les dades obtingudes amb instruments de teledetecció (mesures obtingudes a distància) formen una part essencial en l’àmbit de la meteorologia. Aquestes dades s’obtenen amb diversos sensors de tipus passiu (com els radiòmetres) o actiu (com els radars meteorològics) instal·lats a la superfície terrestre, en avions o en satèl·lits. Els radars meteorològics destinats a observar precipitació operen típicament en longituds d’ona de 3 a 10 cm (bandes X, C i S), realitzen escombrats d’antena en el pla horitzontal i proporcionen una valuosa informació del camp de precipitació en un radi de l’ordre de 100 km, de gran importància en la vigilància i predicció meteorològica a curt termini. La seva posta a punt i manteniment té associat un cost no negligible. També existeixen radars perfiladors, amb antena fixa apuntant el zenit, que proporcionen perfils verticals de precipitació amb gran resolució temporal i espacial. Aquests equips sovint són portables i més econòmics, i permeten realitzar estudis dels processos microfísics que donen lloc a la precipitació, complementant la informació dels radars meteorològics tradicionals. Aquesta tesi es centra en el processament d’observacions de radars perfiladors, concretament en dos tipus d’equips diferents que mitjançant l’efecte Doppler, poden observar la velocitat terminal de caiguda de les partícules de precipitació. La tesi s’estructura en tres blocs i es presenta com a compendi de quatre articles científics. El primer i segon bloc de la tesi es dediquen al perfilador Doppler conegut com Micro Rain Rada, que opera en banda K (longitud d’ona de 1.2 cm) i permet observar precipitació. Al primer bloc es proposa un processament de les dades brutes (reflectivitat espectral) del MRR que contempla diferents algoritmes per detectar pics meteorològics en el senyal, reducció del soroll, i diverses millores per detectar de forma robusta moviments ascendents. A partir d’aquest processament inicial es calculen diversos paràmetres derivats, que permeten estudiar la banda de fusió o “banda brillant” amb una metodologia innovadora. Es presenta un estudi concret, aplicat a un MRR instal·lat a la Facultat de Física de la Universitat de Barcelona al costat de l’estació de radiosondatge del Servei Meteorològic de Catalunya, que s’utilitza com a referència per a la caracterització de la banda brillant. La segona part és un altre estudi aplicat a observacions de MRR durant la campanya Cerdanya-2017 on es proposa una nova metodologia per a classificar diferents tipus de precipitació (com ara pluja, plugim, neu o calamarsa). La metodologia es verifica amb observacions independents de disdròmetre, model Parsivel, (instal·lat al costat del MRR), que proporciona una classificació automàtica de tipus de precipitació. El tercer i darrer bloc de la tesi es centra en el processament d’observacions d’un perfilador de vent Doppler polsat de banda UHF (longitud d’ona d’uns 20 cm), model PCL1300 del fabricant francès Degreane. L’equip està configurat per a funcionar amb cinc feixos per a optimitzar l’estimació de perfils de vent (components horitzontal i vertical). En aquest cas, com en els altres dos blocs anteriors, també es proposa un processat de les dades brutes, però atenent la freqüència de treball, l’equip detecta tant moviments de l’aire com la presència de partícules de precipitació. El processament, a banda d’obtenir el perfil de vent, també és capaç de detectar la precipitació i estimar el tipus de precipitació. Es presenta un estudi amb observacions d’un PCL1300 de Météo- France durant la campanya Cerdanya-2017, on també s’usen dades de MRR i disdròmetre (Parsivel) per a contrastar la nova metodologia proposada. El resultat de cada bloc abordat en aquesta tesis és un programari d’accés lliure, disponible al repositori GitHub, perquè la comunitat científica pugui reutilitzar-lo fàcilment en estudis posteriors.[eng] The first and second blocks of the thesis are devoted to the frequency modulated continuous wave (FMCW) vertically pointing Doppler radar profiler known as Micro Rain Radar from the German manufacturer Metek, which operates in K-band (wavelength of 1.2 cm) and allows precipitation observation. The first block proposes a processing of the raw data (spectral reflectivity) of the MRR that includes different algorithms to detect meteorological peaks in the signal, noise reduction, and several improvements to robustly detect upward movements of the air. From this initial processing, several derived parameters are calculated, which allow the study of the melting band or "bright band" with an innovative methodology. A specific study is presented, applied to a MRR installed at the Faculty of Physics of the University of Barcelona next to the radiosounding station of the Meteorological Service of Catalonia, which is used as a reference for the characterisation of the bright band. The second block is another study applied to MRR observations during the Cerdanya-2017 campaign. The third and last block of the thesis focuses on the processing of observations from a UHF- band pulsed Doppler wind profiler (wavelength about 20 cm), model PCL1300 from the French manufacturer Degreane. The equipment is configured to operate with five beams to optimise the estimation of wind profiles (horizontal and vertical components). In this case, as in the other two previous blocks, processing of the raw data is also proposed, but taking into account the operating frequency, the equipment detects both air movements and the presence of precipitation. The processing, in addition to obtaining the wind profile, is also capable of detecting precipitation and estimating the type of precipitation. A study with observations from a PCL1300 wind profiler of Météo-France, during the Cerdagne-2017 campaign is presented, where MRR and disdrometer (Parsivel) data are also used to validate the new proposed methodology and also it has been used to validate the methodology in the first and second block. The result of each block addressed in this thesis is an open access software, available in the GitHub repository

Remote Sensing of Precipitation: Part II

Precipitation is a well-recognized pillar in the global water and energy balances. The accurate and timely understanding of its characteristics at the global, regional and local scales is indispensable for a clearer insight on the mechanisms underlying the Earth’s atmosphere-ocean complex system. Precipitation is one of the elements that is documented to be greatly affected by climate change. In its various forms, precipitation comprises the primary source of freshwater, which is vital for the sustainability of almost all human activities. Its socio-economic significance is fundamental in managing this natural resource effectively, in applications ranging from irrigation to industrial and household usage. Remote sensing of precipitation is pursued through a broad spectrum of continuously enriched and upgraded instrumentation, embracing sensors which can be ground-based (e.g., weather radars), satellite-borne (e.g., passive or active space-borne sensors), underwater (e.g., hydrophones), aerial, or ship-borne. This volume hosts original research contributions on several aspects of remote sensing of precipitation, including applications which embrace the use of remote sensing in tackling issues such as precipitation estimation, seasonal characteristics of precipitation and frequency analysis, assessment of satellite precipitation products, storm prediction, rain microphysics and microstructure, and the comparison of satellite and numerical weather prediction precipitation products