Vertical profiles of refractivity turbulence structure constant C2n (which is proportional to the radar volume reflectivity) from about 5 to 15 km are measured by the Sunset Radar every 50 seconds. The method of determining such profiles from the radar Doppler spectra is described. The C2n profiles for about an hour are averaged to form (C2n(radar)). The profiles of (C2n(radar)) are quite variable: on the average they decrease by about two orders of magnitude from about 5 to 15 km, and they often change by one order of magnitude from day to day at a given height. A theoretical model is developed that enables the calculation of C2n from routine rawinsonde profiles of wind, temperature, and humidity. This model is based on the assumption that the fluctuations of refractivity that scatter the radio waves are in equilibrium with homogeneous, isotropic, steady‐state turbulence in the inertial subrange. An essential and new feature of this model is an estimate of the mean fraction of the radar‐observed volume that is turbulent. The resulting profiles of (C2n(model)) agree well with the measured profiles of (C2n(radar)) in general shape, in changes from day to day, and in many details from kilometer to kilometer. This agreement implies that: (1) The vertical profile of C2n can be measured by Doppler radar. (2) The vertical profile of C2n can also be estimated by calculation from routine rawinsonde profiles, using our theoretical model.

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Observations from a 16-month field study using two vertically pointing radars and a disdrometer at Wallops Island are analyzed to examine the consistency of the multi-instrument observations with respect to reflectivity and Z-R relations. The vertically pointing radars were operated at S and K bands and had a very good agreement in reflectivity at a gate centered on 175 and 177 m above ground level over a variety of storms. This agreement occurred even though the sampling volumes were of different size and even though the S band measured the reflectivity factor directly, whereas the K-band radar deduced it from attenuated K-band measurements. Indeed, the radar agreement in reflectivity at the collocated range gates was superior to that between the disdrometer and either radar. This is attributed in large part to the spatial separation of the disdrometer and radar sample volumes, although the lesser agreement observed in a prior collocated disdrometer-disdrometer comparison suggests the larger size of the radar sample volumes as well as the better overlap also play a role. Vertical variations in the observations were examined with the aid of the two radar profilers. As expected, the agreement between the disdrometer reflectivity and the reflectivity seen in the vertically pointing radars decreased with height. The effect of these vertical variations on determinations of Z-R relation coefficients was then examined, using a number of different methods for finding the bestfitting coefficients. The coefficient of the Z-R relation derived from paired disdrometer rain rate and radar reflectivity decreased with height, while the exponent of the Z-R relation increased with height. The coefficient and exponent of the Z-R relations also showed sensitivity to the choice of derivation method [linear and nonlinear least squares, fixed exponent, minimizing the root-mean-square difference (RMSD), and probability matching]. The influence of the time lag between the radar and disdrometer measurements was explored by examining the RMSD in reflectivity for paired measurements between 0-and 4-min lag. The nolag conditions had the lowest RMSD up to 400 m, while 1-min lag gave the lowest RMSD at higher heights. The coefficient and exponent of the Z-R relations, on the other hand, did not have a significant change between no-lag-and 1-min-lag-based pairs.

Extreme precipitation events, and the quantitative precipitation forecasts (QPFs) associated with them, are examined. The study uses data from the Hydrometeorology Testbed (HMT), which conducted its first field study in California during the 2005/06 cool season. National Weather Service River Forecast Center (NWS RFC) gridded QPFs for 24-h periods at 24-h (day 1), 48-h (day 2), and 72-h (day 3) forecast lead times plus 24-h quantitative precipitation estimates (QPEs) from sites in California (CA) and Oregon-Washington (OR-WA) are used. During the 172-day period studied, some sites received more than 254 cm (100 in.) of precipitation. The winter season produced many extreme precipitation events, including 90 instances when a site received more than 7.6 cm (3.0 in.) of precipitation in 24 h (i.e., an ''event'') and 17 events that exceeded 12.7 cm (24 h) 21 [5.0 in. (24 h) 21 ]. For the 90 extreme events f.7.6 cm (24 h) 21 [3.0 in. (24 h) 21 ]g, almost 90% of all the 270 QPFs (days 1-3) were biased low, increasingly so with greater lead time. Of the 17 observed events exceeding 12.7 cm (24 h) 21 [5.0 in. (24 h) 21 ], only 1 of those events was predicted to be that extreme. Almost all of the extreme events correlated with the presence of atmospheric river conditions. Total seasonal QPF biases for all events fi.e., $0.025 cm (24 h) 21 [0.01 in. (24 h) 21 ]g were sensitive to local geography and were generally biased low in the California-Nevada River Forecast Center (CNRFC) region and high in the Northwest River Forecast Center (NWRFC) domain. The low bias in CA QPFs improved with shorter forecast lead time and worsened for extreme events. Differences were also noted between the CNRFC and NWRFC in terms of QPF and the frequency of extreme events. A key finding from this study is that there were more precipitation events .7.6 cm (24 h) 21 [3.0 in. (24 h) 21 ] in CA than in OR-WA. Examination of 422 Cooperative Observer Program (COOP) sites in the NWRFC domain and 400 in the CNRFC domain found that the thresholds for the top 1% and top 0.1% of precipitation events were 7.6 cm (24 h) 21 [3.0 in. (24 h) 21 ] and 14.2 cm (24 h) 21 [5.6 in. (24 h) 21 ] or greater for the CNRFC and only 5.1 cm (24 h) 21 [2.0 in. (24 h) 21 ] and 9.4 cm (24 h) 21 [3.7 in. (24 h) 21 ] for the NWRFC, respectively. Similar analyses for all NWS RFCs showed that the threshold for the top 1% of events varies from ;3.8 cm (24 h) 21 [1.5 in. (24 h) 21 ] in the Colorado Basin River Forecast Center (CBRFC) to ;5.1 cm (24 h) 21 [3.0 in. (24 h) 21 ] in the northern tier of RFCs and ;7.6 cm (24 h) 21 [3.0 in. (24 h) 21 ] in both the southern tier and the CNRFC.It is recommended that NWS QPF performance in the future be assessed for extreme events using these thresholds.

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In this paper a five-beam wind profiler and a collocated meteorological tower are used to estimate the accuracy of four-beam and three-beam wind profiler techniques in measuring horizontal components of the wind. In the traditional three-beam technique, the horizontal components of wind are derived from two orthogonal oblique beams and the vertical beam. In the less used four-beam method, the horizontal winds are found from the radial velocities measured with two orthogonal sets of opposing coplanar beams. In this paper the observations derived from the two wind profiler techniques are compared with the tower measurements using data averaged over 30 min. Results show that, while the winds measured using both methods are in overall agreement with the tower measurements, some of the horizontal components of the three-beam-derived winds are clearly spurious when compared with the tower-measured winds or the winds derived from the four oblique beams. These outliers are partially responsible for a larger 30-min, threebeam standard deviation of the profiler/tower wind speed differences (2.2 m s Ϫ1 ), as opposed to that from the four-beam method (1.2 m s Ϫ1 ). It was also found that many of these outliers were associated with periods of transition between clear air and rain, suggesting that the three-beam technique is more sensitive to small-scale variability in the vertical Doppler velocity because of its reliance on the point measurement from the vertical beam, while the four-beam method is surprisingly robust. Even after the removal of the rain data, the standard deviation of the wind speed error from the three-beam method (1.5 m s Ϫ1 ) is still much larger than that from the four-beam method. Taken together, these results suggest that the spatial variability of the vertical airflow in nonrainy periods or hydrometeor fall velocities in rainy periods makes the vertical beam velocities significantly less representative over the area across the three beams, and decreases the precision of the three-beam method. It is concluded that profilers utilizing the four-beam wind profiler technique have better reliability than wind profilers that rely on the three-beam wind profiler technique.

This paper describes a method of absolutely calibrating and routinely monitoring the reflectivity calibration from a scanning weather radar using a vertically profiling radar that has been absolutely calibrated using a collocated surface disdrometer. The three instruments have different temporal and spatial resolutions, and the concept of upscaling is used to relate the small resolution volume disdrometer observations with the large resolution volume scanning radar observations. This study uses observations collected from a surface disdrometer, two profiling radars, and the National Weather Service (NWS) Weather Surveillance Radar-1988 Doppler (WSR-88D) scanning weather radar during the Texas–Florida Underflight-phase B (TEFLUN-B) ground validation field campaign held in central Florida during August and September 1998. The statistics from the 2062 matched profiling and scanning radar observations during this 2-month period indicate that the WSR-88D radar had a reflectivity 0.7 dBZ higher than the disdrometer-calibrated profiler, the standard deviation was 2.4 dBZ, and the 95% confidence interval was 0.1 dBZ. This study implies that although there is large variability between individual matched observations, the precision of a series of observations is good, allowing meaningful comparisons useful for calibration and monitoring.