Use of Ground‐based Radar for Climate‐Scale Studies of Weather and Rainfall

Matyas, Corene J.

doi:10.1111/j.1749-8198.2010.00370.x

Cited by 20 publications

(16 citation statements)

References 155 publications

(305 reference statements)

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“…In grid cells where multiple reflectivity values are available, we performed several experiments and determined that using the highest value from those available is the best solution, as we found that employing a weighted average algorithm leads to a low bias. This may be due to the fact that some stations have a slightly weaker signal [57]. Cells with missing values are filled using the Cressman interpolation [58].…”

Section: Methodsmentioning

confidence: 99%

A Nowcasting Model for Tropical Cyclone Precipitation Regions Based on the TREC Motion Vector Retrieval with a Semi-Lagrangian Scheme for Doppler Weather Radar

Tang

Matyas

2018

Atmosphere

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Accurate observational data and reliable prediction models are both essential to improve the quality of precipitation forecasts. The spiraling trajectories of air parcels within a tropical cyclone (TC) coupled with the large sizes of these systems brings special challenges in making accurate short-term forecasts, or nowcasts. Doppler weather radars are ideal instruments to observe TCs when they move over land, and traditional nowcasts incorporate radar data. However, data from dozens of radars must be mosaicked together to observe the entire system. Traditional single-radar-based reflectivity tracking methods commonly employed in nowcasting are not suitable for TCs as they are not able to capture the circular motion of these systems. Thus, this paper focuses on improving short-term predictability of TC precipitation with Doppler weather radar observations based on: a multi-scale motion vector retrieval algorithm, an optimization technique and a semi-Lagrangian advection scheme. Motion fields of precipitation regions are obtained by a multi-level motion vector retrieval algorithm, then corrected and smoothed by the optimization technique using mass and smooth constraints. Predicted precipitation regions are then extrapolated using the semi-Lagrangian advection scheme. A case study of Hurricane Isabel (2003) shows that the combination of these methods may increase reliable rainfall prediction to about 5 h as the TC moves over land.

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Section: Methodsmentioning

confidence: 99%

A Nowcasting Model for Tropical Cyclone Precipitation Regions Based on the TREC Motion Vector Retrieval with a Semi-Lagrangian Scheme for Doppler Weather Radar

Tang

Matyas

2018

Atmosphere

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“…Overeem et al (2009) derived a 10-year climatology of radar-based rainfall for climatological and hydrological applications. Matyas (2010) has further emphasized the importance of weather radar for such applications. Germann et al (2006) have provided solutions using radars to study orographic precipitation in a rather difficult mountainous region of the Swiss Alps.…”

Section: A Devasthale and L Norin: Radar Observations Of Precipitatmentioning

confidence: 99%

The large-scale spatio-temporal variability of precipitation over Sweden observed from the weather radar network

Devasthale

Norin

2014

Atmos. Meas. Tech.

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Abstract. Using measurements from the national network of 12 weather radar stations for the 11-year period 2000-2010, we investigate the large-scale spatio-temporal variability of precipitation over Sweden. These statistics provide useful information to evaluate regional climate models as well as for hydrology and energy applications. A strict quality control is applied to filter out noise and artifacts from the radar data. We focus on investigating four distinct aspects: the diurnal cycle of precipitation and its seasonality, the dominant timescale (diurnal versus seasonal) of variability, precipitation response to different wind directions, and the correlation of precipitation events with the North Atlantic Oscillation (NAO) and the Arctic Oscillation (AO). When classified based on their intensity, moderate-to high-intensity events (precipitation > 0.34 mm/3 h) peak distinctly during late afternoon over the majority of radar stations in summer and during late night or early morning in winter. Precipitation variability is highest over the southwestern parts of Sweden. It is shown that the high-intensity events (precipitation > 1.7 mm/3 h) are positively correlated with NAO and AO (esp. over northern Sweden), while the low intensity events are negatively correlated (esp. over southeastern parts). It is further observed that southeasterly winds often lead to intense precipitation events over central and northern Sweden, while southwesterly winds contribute most to the total accumulated precipitation for all radar stations. Apart from its operational applications, the present study demonstrates the potential of the weather radar data set for studying climatic features of precipitation over Sweden.

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“…Three radar systems have been deployed along the Tuscan coastal area. Due to the compact size (90 × 130 cm 2 ) and limited weight (about 100 kg), the system can be installed almost everywhere and the installation requirements are practically reduced based on the availability of electric power (the consumption is less than 300 W on average) and the connectivity for data transfer. The radar transmitter is based on a magnetron cavity and on a solid-state modulator.…”

Section: Set Up Of the Radar Systemsmentioning

confidence: 99%

“…Undoubtedly, weather radars are among the most relevant tools for accurately monitoring precipitation events, therefore they are a key instrument for the development of nowcasting and early warning systems. In addition, radar systems have been and still are an indispensable tool for observing weather and increasing the knowledge on precipitation dynamics and hydrometeor statistics [1][2][3][4], subjects of primary interest both in meteorology and in climatology.…”

Section: Introductionmentioning

confidence: 99%

On the Implementation of a Regional X-Band Weather Radar Network

Antonini¹,

Melani

Corongiu³

et al. 2017

Atmosphere

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Abstract:In the last few years, the number of worldwide operational X-band weather radars has rapidly been growing, thanks to an established technology that offers reliability, high performance, and reduced efforts and costs for installation and maintenance, with respect to the more widespread C-and S-band systems. X-band radars are particularly suitable for nowcasting activities, as those operated by the LaMMA (Laboratory of Monitoring and Environmental Modelling for the sustainable development) Consortium in the framework of its institutional duties of operational meteorological surveillance. In fact, they have the capability to monitor precipitation, resolving very local scales, with good spatial and temporal details, although with a reduced scanning range. The Consortium has recently installed a small network of X-band weather radars that partially overlaps and completes the existing national radar network over the north Tyrrhenian area. This paper describes the implementation of this regional network, detailing the aspects related with the radar signal processing chain that provides the final reflectivity composite, starting from the acquisition of the signal power data. The network performances are then qualitatively assessed for three case studies characterised by different precipitation regimes and different seasons. Results are satisfactory especially during intense precipitations, particularly regarding what concerns their spatial and temporal characterisation.

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Use of Ground‐based Radar for Climate‐Scale Studies of Weather and Rainfall

Cited by 20 publications

References 155 publications

A Nowcasting Model for Tropical Cyclone Precipitation Regions Based on the TREC Motion Vector Retrieval with a Semi-Lagrangian Scheme for Doppler Weather Radar

A Nowcasting Model for Tropical Cyclone Precipitation Regions Based on the TREC Motion Vector Retrieval with a Semi-Lagrangian Scheme for Doppler Weather Radar

The large-scale spatio-temporal variability of precipitation over Sweden observed from the weather radar network

On the Implementation of a Regional X-Band Weather Radar Network

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