A fully automated method for the detection and quantification of bird migration was developed for operational C-band weather radar, measuring bird density, speed and direction as a function of altitude. These weather radar bird observations have been validated with data from a high-accuracy dedicated bird radar, which was stationed in the measurement volume of weather radar sites in The Netherlands, Belgium and France for a full migration season during autumn 2007 and spring 2008. We show that weather radar can extract near real-time bird density altitude profiles that closely correspond to the density profiles measured by dedicated bird radar. Doppler weather radar can thus be used as a reliable sensor for quantifying bird densities aloft in an operational setting, which—when extended to multiple radars—enables the mapping and continuous monitoring of bird migration flyways. By applying the automated method to a network of weather radars, we observed how mesoscale variability in weather conditions structured the timing and altitude profile of bird migration within single nights. Bird density altitude profiles were observed that consisted of multiple layers, which could be explained from the distinct wind conditions at different take-off sites. Consistently lower bird densities are recorded in The Netherlands compared with sites in France and eastern Belgium, which reveals some of the spatial extent of the dominant Scandinavian flyway over continental Europe.

Rain gauge data are often employed to estimate the rainfall depth for a given return period. However, the number of rain gauge records of short‐duration rainfall, such as 15 min, is sparse. The obvious advantage of radar data over most rain gauge networks is their higher temporal and spatial resolution. Furthermore, the current quality of quantitative precipitation estimation with radar and the length of the available time series make it feasible to calculate radar‐based extreme rainfall statistics. In this paper an 11‐year radar data set of precipitation depths for durations of 15 min to 24 h is derived for the Netherlands (3.55 × 104 km2). The radar data are adjusted using rain gauges by combining an hourly mean‐field bias adjustment with a daily spatial adjustment. Assuming a generalized extreme value (GEV) distribution, the index flood method is used to describe the distribution of the annual radar rainfall maxima. Regional variability in the GEV location parameter is studied. GEV parameters based on radar and rain gauge data are compared and turn out to be in reasonable agreement. Furthermore, radar rainfall depth‐duration‐frequency (DDF) curves and their uncertainties are derived and compared with those based on rain gauge data. Although uncertainties become large for long durations, it is shown that radar data are suitable to construct DDF curves.

Weather radars give quantitative precipitation estimates over large areas with high spatial and temporal resolutions not achieved by conventional rain gauge networks. Therefore, the derivation and analysis of a radar-based precipitation ''climatology'' are highly relevant. For that purpose, radar reflectivity data were obtained from two C-band Doppler weather radars covering the land surface of the Netherlands ('3.55 3 10 4 km 2 ). From these reflectivities, 10 yr of radar rainfall depths were constructed for durations D of 1, 2, 4, 8, 12, and 24 h with a spatial resolution of 2.4 km and a data availability of approximately 80%. Different methods are compared for adjusting the bias in the radar precipitation depths. Using a dense manual gauge network, a vertical profile of reflectivity (VPR) and a spatial adjustment are applied separately to 24-h (0800-0800 UTC) unadjusted radar-based precipitation depths. Further, an automatic rain gauge network is employed to perform a mean-field bias adjustment to unadjusted 1-h rainfall depths. A new adjustment method is developed (referred to as MFBS) that combines the hourly mean-field bias adjustment and the daily spatial adjustment methods. The record of VPR gradients, obtained from the VPR adjustment, reveals a seasonal cycle that can be related to the type of precipitation. A verification with automatic (D # 24 h) and manual (D 5 24 h) rain gauge networks demonstrates that the adjustments remove the systematic underestimation of precipitation by radar. The MFBS adjustment gives the best verification results and reduces the residual (radar minus rain gauge depth) standard deviation considerably. The adjusted radar dataset is used to obtain exceedance probabilities, maximum rainfall depths, mean annual rainfall frequencies, and spatial correlations. Such a radar rainfall climatology is potentially valuable for the improvement of rainfall parameterization in weather and climate models and the design of hydraulic structures.

Depth-resolved cathodoluminescence spectroscopy of silicon supersaturated with sulfur Appl. Phys. Lett. 102, 031909 (2013) Effect of plasma N2 and thermal NH3 nitridation in HfO2 for ultrathin equivalent oxide thickness J. Appl. Phys. 113, 044103 (2013) Atomic-scale characterization of germanium isotopic multilayers by atom probe tomography J. Appl. Phys. 113, 026101 (2013) Monitoring metal contamination of silicon by multiwavelength room temperature photoluminescence spectroscopy AIP Advances 2, 042164 (2012) Annealing studies of heteroepitaxial InSbN on GaAs grown by molecular beam epitaxy for long-wavelength infrared detectors J. Appl. Phys. 112, 083107 (2012) Additional information on Rev. Sci. Instrum. Trace gas detection of small molecules has been performed with cavity ring down (CRD) absorption spectroscopy in the near UV part of the spectrum. The absolute concentration of the OH radical present in trace amounts in heated plain air due to thermal dissociation of H 2 0 has been calibrated as a function of temperature in the 720-1125 0 C range. Detection of NH 3 at the 10 ppb level is demonstrated in calibrated NH 3 /air flows. Detection of the background Hg concentration in plain air is performed with a current detection limit below 1 ppt. The effect of the laser linewidth in relation to the width of the absorption line is discussed in detail. Basic considerations regarding the use of CRD for trace gas detection are given and it is concluded that CRD spectroscopy holds great promise for sensitive L(sub)-ppbl and fast (kHz) detection of many small molecules.

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has worked to improve harmonization of radar systems and measurements since 1999 and has recently started production of network-wide radar mosaics.

A method to determine the elevation and azimuth biases of the radar antenna using solar signals observed by a scanning radar is presented. Data recorded at low elevation angles where the atmospheric refraction has a significant effect on the propagation of the radio wave are used, and a method to take the effect of the refraction into account in the analysis is presented. A set of equations is given by which the refraction of the radio waves as a function of the relative humidity can easily be calculated. Also, a simplified model for the calculation of the atmospheric attenuation is presented. The consistency of the adopted models for the atmospheric refraction and atmospheric attenuation is confirmed by data collected at a single elevation pointing, but over a long observing time. Finally, the method is applied to datasets based on operational measurements at the Finnish Meteorological Institute (FMI) and Royal Netherlands Meteorological Institute (KNMI), and elevation and azimuth biases of the radars are shown.

[1] An 11 year high-quality radar rainfall data set is used to abstract annual maximum rainfall depths for durations of 15 min to 24 h and area sizes of 6 to 1.7 × 10 3 km 2 for the Netherlands. Generalized extreme value (GEV) distributions are fitted to the annual maxima. A new method is presented to describe the distribution of extreme areal rainfall depths by modeling GEV parameters as a function of both duration and area size. This leads to a semiempirical expression from which quantiles of extreme rainfall depths can be obtained for a chosen duration, area size, and return period. The uncertainties in these quantiles are calculated using the bootstrap method. Radar-based areal reduction factors (ARFs) are derived. These ARFs are comparable to those based on high-density rain gauge networks derived from the literature. It is concluded that radar data, after careful quality control, are suitable to estimate extreme areal rainfall depths.Citation: Overeem, A., T. A. Buishand, I. Holleman, and R. Uijlenhoet (2010), Extreme value modeling of areal rainfall from weather radar, Water Resour. Res., 46, W09514,