Mosaicking Weather Radar Retrievals from an Operational Heterogeneous Network at C and X Band for Precipitation Monitoring in Italian Central Apennines

Abstract

Meteorological radar networks are suited to remotely provide atmospheric precipitation retrieval over a wide geographic area for severe weather monitoring and near-real-time nowcasting. However, blockage due to buildings, hills, and mountains can hamper the potential of an operational weather radar system. The Abruzzo region in central Italy’s Apennines, whose hydro-geological risks are further enhanced by its complex orography, is monitored by a heterogeneous system of three microwave radars at the C and X bands with different features. This work shows a systematic intercomparison of operational radar mosaicking methods, based on bi-dimensional rainfall products and dealing with both C and X bands as well as single- and dual-polarization systems. The considered mosaicking methods can take into account spatial radar-gauge adjustment as well as different spatial combination approaches. A data set of 16 precipitation events during the years 2018–2020 in the central Apennines is collected (with a total number of 32,750 samples) to show the potentials and limitations of the considered operational mosaicking approaches, using a geospatially-interpolated dense network of regional rain gauges as a benchmark. Results show that the radar-network pattern mosaicking, based on the anisotropic radar-gauge adjustment and spatial averaging of composite data, is better than the conventional maximum-value merging approach. The overall analysis confirms that heterogeneous weather radar mosaicking can overcome the issues of single-frequency fixed radars in mountainous areas, guaranteeing a better spatial coverage and a more uniform rainfall estimation accuracy over the area of interest.

Investigating the feasibility of using precipitation measurements from weather RaDAR to estimate potential recharge in regional aquifers: the Majella massif case study in Central Italy

“…RaDAR data represented in the maps are processed with a composite technique that permits better territory coverage and rainfall quantification; some uncertainties can affect these data: orography or strong precipitation can lead to attenuation or even extinction of the backscattered signal (Barbieri et al 2022). Using a composite RaDAR data these issues can be overcome, while orography echoes, ground clutter, can be easily and successfully removed using clutter maps; these are generated detecting ground clutter locations when no rain is present and then used to remove clutter from weather RaDAR measurements (Harrison et al 2000).…”

“…A viable alternative for rainfall measurement are the microwave weather RaDAR (Radio Detection And Ranging) remote sensing systems (Falconi and Marzano 2019), which provide high spatial and temporal frequency dataset of rainfall intensity: RaDAR recordings are typically every 10 minutes and spatial resolution is from 125 m up to 500 m (Barbieri et al 2022). Weather RaDAR allows a real-time estimation of rainfall intensity up to 200 km from the instrument location, identifying the hydrometeors type (i.e., rain, snow, hail) as well as estimating rain cloud velocity and direction.…”

“…Weather RaDAR measurement can be affected by errors as well: ground targets can cause echoes, called "ground clutter", which may be misinterpreted as rainfall such as buildings, hills, and mountains (Falconi and Marzano 2019). These artifacts can be detected by using RaDAR mapping features and mitigated and/or corrected through ad hoc signal processing (Barbieri et al 2022). On the other hand, RaDAR-derived rainfall datasets can provide the reduction of uncertainty about inflow volumes due to its spatial-temporal resolution, which is definitely much higher than rain gauge networks.…”

A Network of X-Band Meteorological Radars to Support the Motorway System (Campania Region Meteorological Radar Network Project)

“…It is important to highlight that the approach of the maximum criterion was selected after the evaluation of other several mosaicking criteria, which involve different methods for the selection of reflectivity values in the overlapping area of two or more radars (e.g., [24][25][26][27][28]). The selection of "maximum value" criterion is motivated by its ease of implementation, which matches the operational requirements of the CARMEN project well.…”

Comparing Rain Gauge and Weather Radar Data in the Estimation of the Pluviometric Inflow from the Apennine Ridge to the Adriatic Coast (Abruzzo Region - Central Italy)

“…On the other hand, weather RaDAR systems (Radio Detection And Ranging, hereafter named "radar" for simplicity) can represent an alternative solution, as they can provide a spatially seamless estimation of rainfall in near real-time. A single weather radar can cover large areas up to 200 km from the radar site with a time sampling of 5-10 min and a spatial range resolution from 125 m up to 500 m [12]. Weather radar estimates of near-surface precipitation can be affected by several limiting factors [13], which includes partial beam blocking from nearby orography, path attenuation caused by the liquid amount along the radar line of sighs, radiofrequency interferences and cone of silence, that is, unobserved areas close to the ground.…”