Estimating reflectivity values from wind turbines for analyzing the potential impact on weather radar services

Locate full-text(opens in a new window)|View at Publisher| Export | Download | More... Atmospheric Measurement Techniques Volume 8, Issue 5, 27 May 2015, Pages 2183-2193 Estimating reflectivity values from wind turbines for analyzing the potential impact on weather radar services (Article) Angulo, I.a, Grande, O.a, Jenn, D.b, Guerra, D.a, De La Vega, D.a a University of the Basque Country (UPV/EHU), Bilbao, Spain b Naval Postgraduate School, Monterey, United States View references (28) Abstract The World Meteorological Organization (WMO) has repeatedly expressed concern over the increasing number of impact cases of wind turbine farms on weather radars. Current signal processing techniques to mitigate wind turbine clutter (WTC) are scarce, so the most practical approach to this issue is the assessment of the potential interference from a wind farm before it is installed. To do so, and in order to obtain a WTC reflectivity model, it is crucial to estimate the radar cross section (RCS) of the wind turbines to be built, which represents the power percentage of the radar signal that is backscattered to the radar receiver.

For the proposed model, a representative scenario has been chosen in which both the weather radar and the wind farm are placed on clear areas; i.e., wind turbines are supposed to be illuminated only by the lowest elevation angles of the radar beam.

This paper first characterizes the RCS of wind turbines in the weather radar frequency bands by means of computer simulations based on the physical optics theory and then proposes a simplified model to estimate wind turbine RCS values. This model is of great help in the evaluation of the potential impact of a certain wind farm on the weather radar operation.

Cloud-radar observations of insects in the UK convective boundary layer

Radar has been applied to the study of insect migration for almost 40 years, but most entomological radars operate at X-band (9.4 GHz, 3.2 cm wavelength), and can only detect individuals of relatively large species, such as migratory grasshoppers and noctuid moths, over all of their flight altitudes. Many insects (including economically important species) are much smaller than this, but development of the requisite higher power and/or higher frequency radar systems to detect these species is often prohibitively expensive. In this paper, attention is focussed upon the uses of some recently-deployed meteorological sensing devices to investigate insect migratory flight behaviour, and especially its interactions with boundary layer processes. Records were examined from the vertically-pointing 35 GHz ‘Copernicus’ and 94 GHz ‘Galileo’ cloud radars at Chilbolton (Hampshire, England) for 12 cloudless and convective occasions in summer 2003, and one of these occasions (13 July) is presented in detail. Insects were frequently found at heights above aerosol particles, which represent passive tracers, indicating active insect movement. It was found that insect flight above the convective boundary layer occurs most often during the morning. The maximum radar reflectivity (an indicator of aerial insect biomass) was found to be positively correlated with maximum screen temperature.

The accuracy of Doppler radar wind retrievals using insects as targets

Insect returns from the UK's Doppler weather radars were collected in the summers of 2007 and 2008, to ascertain their usefulness in providing information about boundary layer winds. Such observations could be assimilated into numerical weather prediction models to improve forecasts of convective showers before precipitation begins. Significant numbers of insect returns were observed during daylight hours on a number of days through this period, when they were detected at up to 30 km range from the radars, and up to 2 km above sea level. The range of detectable insect returns was found to vary with time of year and temperature. There was also a very weak correlation with wind speed and direction. Use of a dual-polarized radar revealed that the insects did not orient themselves at random, but showed distinct evidence of common orientation on several days, sometimes at an angle to their direction of travel. Observation minus model background residuals of wind profiles showed greater bias and standard deviation than that of other wind measurement types, which may be due to the insects' headings/airspeeds and to imperfect data extraction. The method used here, similar to the Met Office's procedure for extracting precipitation returns, requires further development as clutter contamination remained one of the largest error contributors. Wind observations derived from the insect returns would then be useful for data assimilation applications.