Search Results

You are looking at 1 - 10 of 45 items for

  • Author or Editor: Allen White x
  • All content x
Clear All Modify Search
Sergey Y. Matrosov, Robert Cifelli, Allen White, and Timothy Coleman

Abstract

Scanning polarimetric measurements from the operational Weather Surveillance Radar-1988 Doppler (WSR-88D) systems are evaluated for the retrievals of snow-level (SL) heights, which are located below the 0°C isotherm and represent the altitude within the melting layer (ML) where snow changes to rain. The evaluations are conducted by intercomparisons of the SL estimates obtained from the Beale Air Force Base WSR-88D unit (KBBX) during a wet season 6-month period (from October 2012 to March 2013) and robust SL height measurements h SL from a high-resolution vertically pointing Doppler snow-level profiler deployed near Oroville, California. It is shown that a mean value height measurement h L3 between the estimates of the ML top and bottom, which can be derived from the WSR-88D level-III (L3) ML products, provides relatively unbiased estimates of SL heights with a standard deviation of about 165 m. There is little azimuthal variability in derived values of h L3, which is, in part, due to the use of higher radar beam tilts and azimuthal smoothing of the level-III ML products. Height estimates h rho based on detection of the ML minima of the copolar cross-correlation coefficient ρ hv calculated from the WSR-88D level-II products are slightly better correlated with profiler-derived SL heights, though they are biased low by about 113 m with respect to h SL. If this bias is accounted for, the standard deviation of the ρ hv minima–based SL estimates is generally less than 100 m. Overall, the results of this study indicate that, at least for closer radar ranges (up to ~13–15 km), the operational radar polarimetric data can provide snow-level estimates with a quality similar to those from the dedicated snow-level radar profilers.

Full access
Allen B. White, C. W. Fairall, and Dennis W. Thomson

Abstract

Humidity variability at the top of the marine atmospheric boundary layer and in the overlying free troposphere was examined using data collected during the marine stratocumulus phase of the First Regional Experiment (FIRE) of the International Satellite Cloud Climatology Program. A time series of the humidity structure-function parameter C q 2 derived from Doppler wind profiler reflectivity data is compared to a concurrent time series of specific humidity q. Both q and its vertical gradient were calculated from rawinsonde data obtained from sondes launched within 500 m of the profiler. Time-height correlation analysis between log(C q 2) and log(∂q/∂z)2 shows that the two time series are highly correlated at and just above the inversion base, with r approximately equal to 0.7. The correlation is slightly lower in the free troposphere where r is about 0.5 (a value of r greater than 0.2 is significant at the 95% confidence level). There is also correlation between log(C q 2) and log(q), which is maximized at an offset in height between the two instruments.

Closer analysis of a short-lived clearing event shows locally reduced values of C q 2 in a region of enhanced ∂q/∂z. This apparent paradox can be explained by noting the absence of enhanced entrainment associated with cloud-top radiative cooling. The combined wind profiler-rawinsonde datasets were also used to estimate the entrainment velocity w e for clear and cloudy conditions. An average value of w e equal to 0.38 cm s−1 was obtained for cloudy conditions; for the clear case a value of 0.13 cm s−1 was obtained.

Full access
Paul J. Neiman, Daniel J. Gottas, and Allen B. White

Abstract

This observational study of westward-directed gap flows through the Columbia River Gorge uses three radar wind profilers during two winter seasons between October 2015 and April 2017, with a focus on the gap-exit region at Troutdale, Oregon. Of the 92 gap-flow events identified at Troutdale, the mean duration was 38.5 h, the mean gap-jet speed was 12 m s−1, and the mean gap-flow depth was 570 m MSL. The mean gap-jet height and gap-flow depth were situated below the top of the inner gorge, while a maximum depth of 1087 m MSL was contained within the gorge’s outer-wall rim. The mean gap-flow depth was deepest in the cold-air source region east of the gorge and decreased westward to the coast. Strong gap-flow events were longer lived, deeper, and capped by stronger vertical shear than their weak counterparts, and strong (weak) events were forced primarily by a cold-interior anticyclone (offshore cyclone). Deep gap-flow events were longer lived, stronger, and had weaker capping vertical shear than shallow events, and represented a combination of gap-flow and synoptic forcing. Composite temporal analysis shows that gap-flow strength (depth) was maximized midevent (early event), freezing rain was most prevalent during the second half of the event, and accumulated precipitation was greatest late-event. Gap-flow events tended to begin (end) during the evening (morning) hours and were most persistent in January. Surface wind gusts and snow occurrences around Portland, Oregon, were associated primarily with the deepest gap flows, whereas freezing rain occurred predominantly during shallow gap flows.

Free access
David E. Kingsmill, Paul J. Neiman, and Allen B. White

Abstract

This study examines the impact of microphysics regime on the relationship between orographic forcing and orographic rain in the coastal mountains of Northern California using >4000 h of data from profiling Doppler radars, rain gauges, and a GPS receiver collected over 10 cool seasons. Orographic forcing is documented by hourly upslope flow, integrated water vapor (IWV), and IWV flux observed along the coast at Bodega Bay (BBY; 15 m MSL). Microphysics regime is inferred in the coastal mountains at Cazadero (CZC; 478 m MSL), where hourly periods of brightband (BB) and nonbrightband (NBB) rain are designated. BB rain is associated with a microphysics regime dominated by the seeder–feeder process while NBB rain is associated with a microphysics regime dominated by the warm-rain process. Mean BBY upslope flow, IWV, and IWV flux are ~16%, ~5%, and ~19% larger, respectively, for NBB rain compared to BB rain, while mean CZC rain rate is ~33% larger for BB rain compared to NBB rain. The orographic enhancement ratio of CZC to BBY rain rate is 3.7 during NBB rain and 2.7 during BB rain. Rain rate at CZC increases as orographic forcing at BBY increases. For a given amount of BBY orographic forcing, mean CZC rain rates are larger for BB rain compared to NBB rain. Correlation coefficients associated with the relationship between CZC rain rate and BBY orographic forcing are smaller for NBB rain relative to BB rain, but these differences are not statistically significant.

Full access
Allen B. White, C. W. Fairall, and Jack B. Snider

Abstract

Surface-based measurements are used to define some of the important macrophysical and optical properties of marine clouds. These measurements were taken during five different marine field programs. A progression is made from a midlatitude marine stratocumulus regime with an average cloud fraction of 0.7 and a median cloud base of 460 m to a marine tropical regime with an average cloud fraction of 0.2 and a median cloud base of 1050 m. Measurements of the solar transmission coefficient taken during the Atlantic Stratocumulus Transition Experiment (ASTEX) were used in a radiative transfer algorithm to produce values of albedo, absorption, and optical depth. A microwave radiometer provided measurements of the liquid water path (LWP). For a given LWP, the ASTEX optical depths averaged a factor of 2 smaller than the optical depths observed during the marine stratocumulus phase of the First International Cloud Climatology Program Regional Experiment (FIRE) at San Nicolas Island, off the coast of southern California. The variability of boundary-layer aerosol concentrations measured during ASTEX is sufficient to produce a factor of 2 change in optical depth. Further evidence suggests that the cloud droplet effective radius was nearly a factor of 2 larger during ASTFX than during FIRE.

Full access
Brooks E. Martner, Paul J. Neiman, and Allen B. White

Abstract

A strong elevated temperature inversion in a landfalling winter storm in northern California produced two simultaneous melting layers with associated radar bright bands. The storm was observed with scanning and profiling radars. Serial radiosonde launches from the scanning radar site precisely documented the evolving temperature structure of the air mass that produced the double bright band. The radiosonde and radar observations, which were coincident in location and time, clearly illustrate the cause (two melting layers) and effect (two bright bands) of this unusual phenomenon. An automated algorithm for determining the melting-layer height from profiling radar data was tested on this situation. In its operational form, the algorithm detects only the lower melting layer, but in modified form it is capable of detecting both melting layers simultaneously.

Full access
Laura Bianco, James M. Wilczak, and Allen B. White

Abstract

A previous study showed success in determining the convective boundary layer depth with radar wind-profiling radars using fuzzy logic methods, and improvements to the earlier work are discussed. The improved method uses the Vaisala multipeak picking (MPP) procedure to identify the atmospheric signal in radar spectra in place of a fuzzy logic peak picking procedure that was previously used. The method then applies fuzzy logic techniques to calculate the depth of the convective boundary layer. The planetary boundary layer depth algorithm is improved with respect to the one used in the previous study in that it adds information obtained from the small-scale turbulence (vertical profiles of the spectral width of the vertical velocity), while also still using vertical profiles of the radar-derived refractive index structure parameter C 2 n and the variance of vertical velocity. Modifications to the fuzzy logic rules (especially to those using vertical velocity data) that improve the algorithm’s accuracy in cloudy boundary layers are incorporated. In addition, a reliability threshold value to the fuzzy logic–derived score is applied to eliminate PBL depth data values with low score values. These low score values correspond to periods when the PBL structure does not match the conceptual model of the convective PBL built into the algorithm. Also, as a final step, an optional temporal continuity test on boundary layer depth has been developed that helps improve the algorithm’s skill. A comparison with independent boundary layer depth estimations made “by eye” by meteorologists at two radar wind-profiler sites, significantly different in their characteristics, shows that the new improved method gives significantly more accurate estimates of the boundary layer depth than does the previous method, and also much better estimates than the simpler “standard” method of selecting the peak of C 2 n. The new method produces an absolute error of the mixing-depth estimates comparable to the vertical range resolution of the profilers.

Full access
Allen B. White, Daniel J. Gottas, Eric T. Strem, F. Martin Ralph, and Paul J. Neiman

Abstract

Because knowledge of the melting level is critical to river forecasters and other users, an objective algorithm to detect the brightband height from profiles of radar reflectivity and Doppler vertical velocity collected with a Doppler wind profiling radar is presented. The algorithm uses vertical profiles to detect the bottom portion of the bright band, where vertical gradients of radar reflectivity and Doppler vertical velocity are negatively correlated. A search is then performed to find the peak radar reflectivity above this feature, and the brightband height is assigned to the altitude of the peak. Reflectivity profiles from the off-vertical beams produced when the radar is in the Doppler beam swinging mode provide additional brightband measurements. A consensus test is applied to subhourly values to produce a quality-controlled, hourly averaged brightband height. A comparison of radar-deduced brightband heights with melting levels derived from temperature profiles measured with rawinsondes launched from the same radar site shows that the brightband height is, on average, 192 m lower than the melting level. A method for implementing the algorithm and making the results available to the public in near–real time via the Internet is described. The importance of melting level information in hydrological prediction is illustrated using the NWS operational river forecast model applied to mountainous watersheds in California. It is shown that a 2000-ft increase in the melting level can triple run off during a modest 24-h rainfall event. The ability to monitor the brightband height is likely to aid in melting-level forecasting and verification.

Full access
Paul J. Neiman, Daniel J. Gottas, Allen B. White, Lawrence J. Schick, and F. Martin Ralph

Abstract

Two vertically pointing S-band radars (coastal and inland) were operated in western Washington during two winters to monitor brightband snow-level altitudes. Similar snow-level characteristics existed at both sites, although the inland site exhibited lower snow levels by ~70 m because of proximity to cold continental air, and snow-level altitude changes were delayed there by several hours owing to onshore translation of weather systems. The largest precipitation accumulations and rates occurred when the snow level was largely higher than the adjacent terrain. A comparison of these observations with long-term operational radiosonde data reveals that the radar snow levels mirrored climatological conditions. The inland radar data were used to assess the performance of nearby operational freezing-level forecasts. The forecasts possessed a lower-than-observed bias of 100–250 m because of a combination of forecast error and imperfect representativeness between the forecast and observing points. These forecast discrepancies increased in magnitude with higher observed freezing levels, thus representing the hydrologically impactful situations where a greater fraction of mountain basins receive rain rather than snow and generate more runoff than anticipated. Vertical directional wind shear calculations derived from wind-profiler data, and concurrent surface temperature data, reveal that most snow-level forecast discrepancies occurred with warm advection aloft and low-level cold advection through the Stampede Gap. With warm advection, forecasts were too high (low) for observed snow levels below (above) 1.25 km MSL. An analysis of sea level pressure differences across the Cascades indicated that mean forecasts were too high (low) for observed snow levels below (above) 1.25 km MSL when higher pressure was west (east) of the range.

Full access
Sergey Y. Matrosov, F. Martin Ralph, Paul J. Neiman, and Allen B. White

Abstract

An evaluation of Weather Surveillance Radar-1988 Doppler (WSR-88D) KMUX and KDAX radar quantitative precipitation estimation (QPE) over a site in California’s northern Sonoma County is performed and rain type climatology is presented. This site is next to the flood-prone Russian River basin and, because of the mountainous terrain and remoteness from operational radars, is generally believed to lack adequate coverage. QPE comparisons were conducted for multiyear observations with concurrent classification of rainfall structure using measurements from a gauge and an S-band profiler deployed at the location of interest. The radars were able to detect most of the brightband (BB) rain, which contributed over half of the total precipitation. For this rain type hourly radar-based QPE obtained with a default vertical profile of reflectivity correction provided results with errors of about 50%–60%. The operational radars did not detect precipitation during about 30% of the total rainy hours with mostly shallow nonbrightband (NBB) rain, which, depending on the radar, provided ~(12%–15%) of the total precipitation. The accuracy of radar-based QPE for the detected fraction of NBB rain was rather poor with large negative biases and characteristic errors of around 80%. On some occasions, radars falsely detected precipitation when observing high clouds, which did not precipitate or coexisted with shallow rain (less than 10% of total accumulation). For heavier rain with a significant fraction of BB hourly periods, radar QPE for event totals showed relatively good agreement with gauge data. Cancelation of errors of opposite signs contributed, in part, to such agreement. On average, KDAX-based QPE was biased low compared to KMUX.

Full access