Abstract

Abstract. The RadAlp experiment aims at developing advanced methods for rainfall and snowfall estimation using weather radar remote sensing techniques in high mountain regions for improved water resource assessment and hydrological risk mitigation. A unique observation system has been deployed since 2016 in the Grenoble region of France. It is composed of an X-band radar operated by Météo-France on top of the Moucherotte mountain (1901 m above sea level; hereinafter MOUC radar). In the Grenoble valley (220 m above sea level; hereinafter a.s.l.), we operate a research X-band radar called XPORT and in situ sensors (weather station, rain gauge and disdrometer). In this paper we present a methodology for studying the relationship between the differential phase shift due to propagation in precipitation (Φdp) and path-integrated attenuation (PIA) at X band. This relationship is critical for quantitative precipitation estimation (QPE) based on polarimetry due to severe attenuation effects in rain at the considered frequency. Furthermore, this relationship is still poorly documented in the melting layer (ML) due to the complexity of the hydrometeors' distributions in terms of size, shape and density. The available observation system offers promising features to improve this understanding and to subsequently better process the radar observations in the ML. We use the mountain reference technique (MRT) for direct PIA estimations associated with the decrease in returns from mountain targets during precipitation events. The polarimetric PIA estimations are based on the regularization of the profiles of the total differential phase shift (Ψdp) from which the profiles of the specific differential phase shift on propagation (Kdp) are derived. This is followed by the application of relationships between the specific attenuation (k) and the specific differential phase shift. Such k–Kdp relationships are estimated for rain by using drop size distribution (DSD) measurements available at ground level. Two sets of precipitation events are considered in this preliminary study, namely (i) nine convective cases with high rain rates which allow us to study the ϕdp–PIA relationship in rain, and (ii) a stratiform case with moderate rain rates, for which the melting layer (ML) rose up from about 1000 up to 2500 m a.s.l., where we were able to perform a horizontal scanning of the ML with the MOUC radar and a detailed analysis of the ϕdp–PIA relationship in the various layers of the ML. A common methodology was developed for the two configurations with some specific parameterizations. The various sources of error affecting the two PIA estimators are discussed, namely the stability of the dry weather mountain reference targets, radome attenuation, noise of the total differential phase shift profiles, contamination due to the differential phase shift on backscatter and relevance of the k–Kdp relationship derived from DSD measurements, etc. In the end, the rain case study indicates that the relationship between MRT-derived PIAs and polarimetry-derived PIAs presents an overall coherence but quite a considerable dispersion (explained variance of 0.77). Interestingly, the nonlinear k–Kdp relationship derived from independent DSD measurements yields almost unbiased PIA estimates. For the stratiform case, clear signatures of the MRT-derived PIAs, the corresponding ϕdp value and their ratio are evidenced within the ML. In particular, the averaged PIA∕ϕdp ratio, a proxy for the slope of a linear k–Kdp relationship in the ML, peaks at the level of the copolar correlation coefficient (ρhv) peak, just below the reflectivity peak, with a value of about 0.42 dB per degree. Its value in rain below the ML is 0.33 dB per degree, which is in rather good agreement with the slope of the linear k–Kdp relationship derived from DSD measurements at ground level. The PIA∕ϕdp ratio remains quite high in the upper part of the ML, between 0.32 and 0.38 dB per degree, before tending towards 0 above the ML.

Highlights

  • Estimation of atmospheric precipitation is important in a high mountain region such as the Alps for the assessment and management of water and snow resources for drinking water, hydropower production, agriculture and tourism characterized by high seasonal variability

  • Before presenting the analysis of the φdp–path-integrated attenuation (PIA) relationship in rain and in the melting layer based on the estimates for all the mountain targets and time steps available for the two sets of events, we study in this subsection the k–Kdp relationships that we were able to derive from the drop size distribution (DSD) measurements collected at ground level at the Institute of Environmental Geosciences (IGE) site

  • In this work we developed a methodology for studying the relationship between total differential phase shift and path-integrated attenuation (PIA) at X band

Read more

Summary

Introduction

Estimation of atmospheric precipitation (solid/liquid) is important in a high mountain region such as the Alps for the assessment and management of water and snow resources for drinking water, hydropower production, agriculture and tourism characterized by high seasonal variability. One of the most critical applications concerns the prediction of natural hazards associated with intense precipitation and melting of snowpacks, i.e., inundations, floods, flash floods and gravitational movements, which requires a high-resolution observation, namely spatial resolution ≤ 1 km and temporal resolution ≤ 1 h. While this can hardly be achieved over extended areas with traditional in situ rain gauge networks, the use of radar remote sensing has a high potential that needs to be exploited and a number of limitations that need to be surpassed. On the other hand, installing a radar at the bottom of the valley provides high-resolution and quality data required for vulnerable and densely populated Alpine valleys, but the QPEs are limited in the latter due to beam blockage by surrounding mountains

Objectives
Methods
Results
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.