Marco Gabella

A Comparison between the GPM Dual-Frequency Precipitation Radar and Ground-Based Radar Precipitation Rate Estimates in the Swiss Alps and Plateau

AbstractThe Global Precipitation Measurement (GPM) mission Dual-Frequency Precipitation Radar (DPR) provides a unique set of three-dimensional radar precipitation estimates across much of the globe. Both terrain and climatic conditions can have a strong influence on the reliability of these estimates. Switzerland provides an ideal testbed to evaluate the performance of the DPR in complex terrain: it consists of a mixture of very complex terrain (the Alps) and the far flatter Swiss Plateau. It is also well instrumented, covered with a dense gauge network as well as a network of four dual-polarization C-band weather radars, with the same instrument network used in both the Plateau and the Alps. Here an evaluation of the GPM DPR rainfall rate products against the MeteoSwiss radar rainfall rate product for the first two years of the GPM DPR’s operation is presented. Errors in both detection and estimation are considered, broken down by terrain complexity, season, precipitation phase, precipitation type, and p...

A Network of Portable, Low-Cost, X-Band Radars

Radar is a unique tool to get an overview on the weather situation, given its high spatio- temporal resolution. Over 60 years, researchers have been investigating ways for obtaining the best use of radar. As a result we often find assurances on how much radar is a useful tool, and it is! After this initial statement, however, regularly comes a long list on how to increase the accuracy of radar or in what direction to move for improving it. Perhaps we should rather ask: is the resulting data good enough for our application? The answers are often more complicated than desired. At first, some people expect miracles. Then, when their wishes are disappointed, they discard radar as a tool: both attitudes are wrong; radar is a unique tool to obtain an excellent overview on what is happening: when and where it is happening. At short ranges, we may even get good quantitative data. But at longer ranges it may be impossible to obtain the desired precision, e.g. the precision needed to alert people living in small catchments in mountainous terrain. We would have to set the critical limit for an alert so low that this limit would lead to an unacceptable rate of false alarms

FIREcast system - Previsional fire danger index computation system for alpine regions

FIREcast is a previsional fire danger index computing system, which elaborates weather parameter maps to evaluate the danger indicator on the interest area. FIREcast uses as a starting point the foreseen Canadian Fire Weather Index (FWI) adjusted for continental European latitudes and climatology and adapted for alpine regions orography. As FWI is a meteorological fire danger index, it represents the fire danger level due solely to the present and past weather conditions, not considering contingent human presence and actions. FIREcast operates on meteorological forecast input data maps, to obtain output maps representing expected fire danger in the studied area (Piedmont criteria in the current case) with a forecasting time interval up to 72 hours, after adjusting the forecast to historical fire records. FIREcast is a valuable aid in firefighting management: it allows involved agencies to have an efficient resources administration (both logistic and human), well aimed territory monitoring and reliable intervention planning for operators’ safety.

Towards sustainable agricultural management using highresolution X-band radar precipitation estimates

This contribution deals with the technological aspects of a research funded in the framework of a Scientific Cooperation program between Italy and Israel. The aim of this research is to evaluate if real-time estimates of precipitation at high spatial and temporal resolution can significantly improve the efficiency of agricultural management by optimizing agronomic practices from an economical and environmental standpoint. The preliminary data analysis and radar calibration strategy necessary for a correct estimation of rain fields is here presented for all the radar installations involved in the research.

Rainfall estimation improvements using polarization data from Monte Lema C-band weather radar in the southern European alps

Simple improvements in C-band weather radar data processing are performed based on radar polarimetry. The starting point is the estimation of the differential propagation phase Φ_DP from the measured total differential phase Ψ_DP. The main topics are (ground) clutter removal and quantitative precipitation estimation (QPE). For the former, a new test which checks some polarimetric quantities is added (as a trial) in a pre-existing clutter/non-clutter bin classification system. For the latter, three `state-of-the-art Φ_DP-based precipitation attenuation correction procedures are considered to correct Z_H for precipitation attenuation. In addition, since the specific differential phase K_DP proves to be a better rainfall rate estimator in heavy rain, some hybrid formulas R(Z_H, K_DP) are developed so that they result practically unbiased.

Acceptance tests and monitoring of the next generation polarimetric weather radar network in Switzerland

MeteoSwiss has recently renewed its weather radar network with an innovative state-of-the-art solution. The main reason for such renewal was the end-of-life of the existing radar systems. During both the acceptance tests and the current operational working time, carefully planned, innovative measurements have being performed on site using both a passive and an active calibrators.

High resolution X-Band radar rainfall estimates for a Mediterranean to hyper-arid transition area

This study investigates the quantitative accuracy of two X-Band weather radars recently installed in the Northern Negev (Israel). The area raises interest due to its strong climatological gradient that, in less than 100 km, ranges from Mediterranean, where land is extensively used for agriculture, to arid, where flash floods often cause casualties and damage. Rainfall estimates from the X-Band radars are processed in order to correct the effects of i) ground echoes, ii) beam blockage and iii) attenuation of the radar beam. Measures from a relatively sparse raingauge network (~1/200 km-2) and a carefully corrected C-Band weather radar are used as a reference to quantify the accuracy of X-Band rainfall estimates on a set of rainfall events occurred during the first years of measurements.

Characterisation of the melting layer variability in an Alpine valley based on polarimetric X-band radar scans

The melting layer designates the transition region from solid to liquid precipitation, and is a typical feature of the vertical structure of stratiform precipitation. As it is characterised by a well-known signature in polarimetric radar variables, it can be identified by automatic detection algorithms. Though often assumed to be uniform in space and time for applications such as vertical profile correction, the spatial variability of the melting layer remains poorly documented. This work undertakes to characterise and quantify the spatial and temporal variability of the melting layer using a method based on the Fourier 5 transform, which is applied to high resolution X-band polarimetric radar data from two measurement campaigns in Switzerland. It is first demonstrated that the proposed method can accurately and concisely describe the spatial variability of the melting layer and may therefore be used as a tool for comparison. The method is then used to characterise the melting layer variability in summer precipitation on the relatively flat Swiss plateau and in winter precipitation in a large inner Alpine valley (the Rhone valley in the Swiss Alps). Results indicate a higher contribution of smaller spatial scales to the total melting layer variability in 10 the case of the Alpine environment. The same method is also applied on data from vertical scans in order to study the temporal variability of the melting layer. The variability in space and time is then compared to investigate the spatio-temporal coherence of the melting layer variability in the two study areas, which was found to be more consistent with the assumption of pure advection for the case of the plateau.

Retrieval of atmospheric refractivity profiles from ground-based GPS measurements

An alternative remote sensing technique for the retrieval of atmospheric refractive index profiles is presented. It is an optimization procedure for the inversion of ground-based GPS phase measurements collected at low elevation angles. The Abel inversion, usually adopted to infer atmospheric profiles from space-based radio occultation observations, cannot be applied to the inversion of ground-based measurements. Therefore, we propose a technique which iteratively looks for the refractive index profile by minimizing a cost function. This function depends on several measurements of signal times-of-flight, provided that the correspondent real signal arrival angles could be known with sufficient accuracy. Although different optimization procedures could be used, a non-linear least squares procedure has been adopted in this first attempt. Starting from a different first guess profile, the retrieved refractivity profile is in good agreement with the reference one, which is used to derive the observables.