Lengfeld, K.; Clemens, M.; Merker, C.; Münster, H.; Ament, F. Journal of atmospheric and oceanic technology Vol. 33, num. 11, p. 2315-2329 DOI: 10.1175/JTECH-D-15-0091.1 Data de publicació: 2016-11 Article en revista
This paper presents a novel, simple method to correct reflectivity measurements of weather radars that operate in attenuation-influenced frequency bands using observations from less attenuated radar systems. In recent years radar systems operating in the X-band frequency range have been developed to provide precipitation fields for areas of special interest in high temporal (=1 min) and spatial (=250 m) resolution in complement to nationwide radar networks. However, X-band radars are highly influenced by attenuation. C- and S-band radars typically have coarser resolution (250 m–1 km and 5 min) but are less affected by attenuation.
Correcting for attenuation effects in simple (non-Doppler) single-polarized X-band radars remains challenging and is often dependent on restriction parameters, for example, those derived from mountain returns. Therefore, these algorithms are applicable only in limited areas. The method proposed here uses measurements from C-band radars and hence can be applied in all regions covered by nationwide C- (or S-) band radar networks. First, a single scan of X-band radar measurements is used exemplary to identify advantages and disadvantages of the novel algorithm compared to a standard single radar algorithm. The performance of the correction algorithms in different types of precipitation is examined in nine case studies. The proposed method provides very promising results for each type of precipitation. Additionally, it is evaluated in a 5-month comparison with Micro Rain Radar (MRR) observations. The bias between uncorrected X-band radar and MRR data is nearly eliminated by the attenuation correction algorithm, and the RMSE is reduced by 20% while the correlation of ~0.9 between both systems remains nearly constant.
Bricheno, L.M.; Soret, A.; Wolf, J.; Jorba, O.; Baldasano, J. Journal of atmospheric and oceanic technology Vol. 30, num. 6, p. 1021-1037 DOI: 10.1175/JTECH-D-12-00087.1 Data de publicació: 2013-06-01 Article en revista
Accurate representation of wind forcing and mean sea level pressure is important for modeling waves and
surges. This is especially important for complex coastal zone areas. The Weather Research and Forecasting
(WRF) model has been run at 12-, 4-, and 1.33-km resolution for a storm event over the Irish Sea. The outputs
were used to force the coupled hydrodynamic and the Proudman Oceanographic Laboratory Coastal Ocean
Modeling System (POLCOMS)–Wave Model (WAM) and the effect on storm surge and waves has been
assessed. An improvement was observed in the WRF model pressure and wind speed when moving from
12- to 4-km resolution with errors in wind speed decreasing more than 10% on average. When moving from
4 to 1.33km no further significant improvement was observed. The atmospheric model results at 12 and 4 km
were then applied to the ocean model. Wave direction was seen to improve with increased ocean model
resolution, and higher-resolution forcing was found to generally increase the wave height over the Irish Sea by
up to 40cm in places. Improved clustering of wave direction was observed when 4-km meteorological forcing
was used. Large differences were seen in the coastal zone because of the improved representation of the
coastline and, in turn, the atmospheric boundary layer. The combination of high-resolution atmospheric
forcing and a coupled wave–surge model gave the best result.
Identification of aerosol layers on lidar measurements is of interest to determine ranges where aerosol properties are likely to be homogeneous and to infer transport phenomena and atmosphere dynamics. For instance, the range-corrected backscattered signal from aerosol measured with lidars has long been used as a proxy to determine the depth of the planetary boundary layer. The method relies on the assumption that in a well-mixed atmosphere, a rather homogenous aerosol distribution will exist within the boundary layer; hence, a sudden drop in the lidar range-corrected signal profile will mark the end of the layer. The most usual methods to detect that drop are the gradient method, which detects a negative maximum in the derivative with respect to range of the lidar range-corrected signal, or of its logarithm, and the wavelet correlation transform method, which detects a maximum in the correlation function of the lidar range-corrected signal and a wavelet, usually the Haar wavelet. These methods are not restricted to determining the boundary layer height but can also be used to locate the edges of lofted aerosol layers. Using fundamentals of linear system theory, this study shows the deep link existing between the gradient method and the wavelet correlation transform method using the Haar wavelet, the latter being equivalent to the gradient method applied to a range-corrected signal profile smoothed by a low-pass spatial filtering, which seems not to have been explicitly noted in the literature so far. Consequences are readily drawn for the wavelet correlation transform method using other wavelets.
Talone, M.; Gabarro, C.; Camps, A.; Sabia, R.; Gourrion, J.; Vall-llossera, M.; Font, J. Journal of atmospheric and oceanic technology Vol. 28, num. 9, p. 1155-1166 DOI: 10.1175/2011.JTECHO813.1 Data de publicació: 2011-09 Article en revista
The vertical gradient of refractivity (dN/dh) determines the path of the radar beam; namely, the larger the negative values of the refractivity gradient, the more the beam bends toward the ground. The variability of the propagation conditions significantly affects the coverage of the ground echoes and, thus, the quality of the scanning radar measurements. The information about the vertical gradient of refractivity is usually obtained from radiosonde soundings whose use, however, is limited by their coarse temporal and spatial resolution. Because radar ground echo coverage provides clues about how severe the beam bending can be, we have investigated a method that uses radar observations to infer propagation conditions with better temporal resolution than the usual soundings.
Using the data collected during the International H2O Project (IHOP_2002), this simple method has shown some skill in capturing the propagation conditions similar to these estimated from soundings. However, the evaluation of the method has been challenging because of 1) the limited resolution of the conventional soundings in time and space, 2) the lack of other sources of data with which to compare the results, and 3) the ambiguity in the separation of ground from weather echoes
The radar refractivity retrieval algorithm applied to radar phase measurements from ground targets can provide high-resolution, near-surface moisture estimates in time and space. The reliability of the retrieval depends on the quality of the returned phase measurements, which are affected by factors such as 1) the vertical variation of the refractive index along the ray path and 2) the properties of illuminated ground targets (e.g., the height and shape of the targets intercepted by radar rays over complex terrain). These factors introduce ambiguities in the phase measurement that have not yet been considered in the refractivity algorithm and that hamper its performance.
A phase measurement simulator was designed to better understand the effect of these factors. The results from the simulation were compared with observed phase measurements for selected atmospheric propagation conditions estimated from low-level radio sounding profiles. Changes in the vertical gradient of refractivity coupled with the varying heights of targets are shown to have some influence on the variability of phase fields. However, they do not fully explain the noisiness of the real phase observations because other factors that are not included in the simulation, such as moving ground targets, affect the noisiness of phase measurements.
Berenguer, M.; Sempere-Torres, D.; Corral, C.; Sanchez-Diezma, R. Journal of atmospheric and oceanic technology Vol. 23, num. 9, p. 1157-1180 DOI: 10.1175/JTECH1914.1 Data de publicació: 2006-09 Article en revista
Because echoes caused by nonmeteorological targets significantly affect radar scans, contaminated bins must be identified and eliminated before precipitation can be quantitatively estimated from radar measurements. Under mean propagation conditions, clutter echoes (mainly caused by targets such as mountains or large
buildings) can be found in almost fixed locations. However, in anomalous propagation conditions, new clutter echoes may appear (sometimes over the sea), and they may be difficult to distinguish from precipitation
returns. Therefore, an automatic algorithm is needed to identify clutter on radar scans, especially for operational uses of radar information (such as real-time hydrology). In this study, a new algorithm is presented based on fuzzy logic, using volumetric data. It uses some statistics to highlight clutter characteristics (namely, shallow vertical extent, high spatial variability, and low radial velocities) to output a value that quantifies the possibility of each bin being affected by clutter (in order to remove those in which this factor exceeds a certain threshold).
The performance of this algorithm was compared against that of simply removing mean clutter echoes. Satisfactory results were obtained from an exhaustive evaluation of this algorithm, especially in those cases
in which anomalous propagation played an important role.
Legrand, M.; Pietras, C.; Brogniez, G.; Haeffelin, M.; Abuhassan, N.; Sicard, M. Journal of atmospheric and oceanic technology Vol. 17, num. 9, p. 1203-1214 Data de publicació: 2000-09 Article en revista
Sempere-Torres, D.; Salles, C.; Creutin, J.-D. Journal of atmospheric and oceanic technology Vol. 15, p. 1215-1222 DOI: 10.1175/1520-0426(1998)015<1215:TOSR>2.0.CO;2 Data de publicació: 1998-10 Article en revista
The optical spectropluviometer is a shadowgraph instrument able to measure independently the equivalent diameter and the fall speed of raindrops at ground level. Hardware and software modifications are proposed and tested. A modern digital signal processing system allows for the simultaneous sampling and analyzing of the signal delivered by the sensor. The IR light transmission is pulsed to avoid interference with natural radiation and the protection of the optics is improved. The validation procedure consists of comparing the rain rates derived from the measured drop size distributions with rain rates delivered by nearby rain gauges. The results obtained during 65 storm events show that the proposed improvements reduce the bias of the rain-rate estimation from 34% to 16%. Suggestions are given to further improve the performance of this instrument.