During the first Wind Forecast Improvement Project (WFIP), new meteorological observations were collected from a large suite of instruments, including wind velocities measured on networks of tall towers provided by wind industry partners, wind speeds measured by cup anemometers mounted on the nacelles of wind turbines, and wind profiles by networks of Doppler sodars and radar wind profilers. Previous data denial studies found a significant improvement of up to 6% root mean squared error (RMSE) reduction for short-term wind power forecasts due to the assimilation of all of these observations into the National Oceanic and Atmospheric Administration (NOAA) Rapid Refresh (RAP) forecast model using a 3D variational data assimilation scheme. As a follow-on study, we now investigate the impacts of assimilating into the RAP model either the additional remote sensing observations (sodars and radar wind profilers) alone or assimilating the industry-provided in situ observations (tall towers and nacelle anemometers) alone, in addition to routinely available standard meteorological data sets. The more numerous tall tower/nacelle observations provide a relatively large improvement through the first 3 to 4 hours of the forecasts, which diminishes to a negligible impact by forecast hour 6. In comparison, the sparser vertical profiling sodars/radars provide an initially smaller impact that decays at a much slower rate, with a positive impact present through the first 12 hours of the forecast. Large positive assimilation impacts for both sets of instruments are found during daytime hours, while small or even negative impacts are found during nighttime hours.

The Second Wind Forecast Improvement Project (WFIP2) is a U.S. Department of Energy (DOE)- and National Oceanic and Atmospheric Administration (NOAA)-funded program, with private-sector and university partners, which aims to improve the accuracy of numerical weather prediction (NWP) model forecasts of wind speed in complex terrain for wind energy applications. A core component of WFIP2 was an 18-month field campaign that took place in the U.S. Pacific Northwest between October 2015 and March 2017. A large suite of instrumentation was deployed in a series of telescoping arrays, ranging from 500 km across to a densely instrumented 2 km x 2 km area similar in size to a high-resolution NWP model grid cell. Observations from these instruments are being used to improve our understanding of the meteorological phenomena that affect wind energy production in complex terrain and to evaluate and improve model physical parameterization schemes. We present several brief case studies using these observations to describe phenomena that are routinely difficult to forecast, including wintertime cold pools, diurnally driven gap flows, and mountain waves/wakes. Observing system and data product improvements developed during WFIP2 are also described.

A roadway toxics dispersion study was conducted at the Idaho National Laboratory to document the effects on concentrations of roadway emissions behind a roadside sound barrier in various conditions of atmospheric stability. The key finding was that reduced concentrations were measured behind the barrier in all stability conditions. It was also found that the magnitude of the concentration footprint behind the barrier was tied to atmospheric stability and that the roadway tended to trap high concentrations during light wind speed conditions.

Since the 1980s, there have been few improvements to line-source dispersion parameterizations in operational dispersion models. Under EPA's Near-Roadway Research Initiative, research to characterize dispersion near major roadways has experienced a resurgence. This paper summarizes an integrated study involving wind tunnel experiments, ambient field measurements, an SF(6) tracer field study, and numerical model development and application. The focus of the study has been to assess the impact of common roadway configurations, such as road cuts and noise barriers. In particular, the impact of noise barriers, which are common features along major roadways in the United States, is being examined. Results to date indicate that noise barriers significantly enhance dispersion of pollutants near major roadways.

A roadway toxics dispersion study was conducted at the Idaho National Laboratory (INL) to document the effects on concentrations of roadway emissions behind a roadside sound barrier in various conditions of atmospheric stability. The homogeneous fetch of the INL, controlled emission source, lack of other manmade or natural flow obstructions, and absence of vehicle-generated turbulence reduced the ambiguities in interpretation of the data. Roadway emissions were simulated by the release of an atmospheric tracer (SF(6)) from two 54 m long line sources, one for an experiment with a 90 m long noise barrier and one for a control experiment without a barrier. Simultaneous near-surface tracer concentration measurements were made with bag samplers on identical sampling grids downwind from the line sources. An array of six 3-d sonic anemometers was employed to measure the barrier-induced turbulence. Key findings of the study are: (1) the areal extent of higher concentrations and the absolute magnitudes of the concentrations both increased as atmospheric stability increased; (2) a concentration deficit developed in the wake zone of the barrier with respect to concentrations at the same relative locations on the control experiment at all atmospheric stabilities; (3) lateral dispersion was significantly greater on the barrier grid than the non-barrier grid; and (4) the barrier tended to trap high concentrations near the "roadway" (i.e. upwind of the barrier) in low wind speed conditions, especially in stable conditions. Published by Elsevier Ltd.

A 2006 article in Boundary-Layer Meteorology by G. Treviño and E.L Andreas presents a derivation that questions the use of time averaging for computing turbulence statistics. Their derivation shows that time averaging over a finite interval always leads to a zero integral time scale. As a result, Treviño and Andreas argue that any turbulence quantities derived from time averaging are tainted and incompatible with the Navier–Stokes equations. While Treviño and Andreas are correct that time averaging does produce integral scales that are quite different from what researchers commonly expect, this comment demonstrates that the theoretical implications are not as dire as they claim.

Turbulence and air-surface exchange are important factors throughout the life cycle of a tropical cyclone. Conventional turbulence instruments are not designed to function in the extreme environment encountered in such storms. A new instrument called the Extreme Turbulence (ET) probe has been developed specifically for measuring turbulence on a fixed tower in hurricane conditions. Although the probe is designed for surface deployment, it is based on the same pressure-sphere technology used for aircraft gust probes.The ET probe is designed around a 43-cm-diameter sphere with 30 pressure ports distributed over its surface. A major obstacle during development was finding a method to prevent water from fouling the pressure ports. Two approaches were investigated: a passive approach using gravity drainage and an active approach using an air pump to flush water from the ports. The probes were tested in both dry and wet conditions by mounting them on a vehicle side by side with more conventional instruments. In dry conditions, test data from the ET probes were in good agreement. with the conventional instruments. In rain, probes using the passive rain defense performed about as well as in dry conditions, with the exception of some water intrusion into the temperature sensors. The active rain defense has received only limited attention so far, mainly because of the success and simplicity of the passive defense.

The Tennessee River Valley in the eastern part of Tennessee is a broad valley with a moist climate and extensive forest cover. A series of 50-100-m-high parallel ridges forms corrugations along the floor of the valley. Tower measurements and numerical simulations are used in this paper to study the channeling of the winds in this valley over the diurnal cycle. At night, pressure-driven channeling caused by geostrophic imbalances is often present, but this channeling tends to be concentrated on the leeward side of the valley (relative to the winds aloft). The channeling is significantly weaker during the afternoon, so the winds on top of the corrugations are more closely aligned with those aloft. In the bottomlands between the corrugations, however, the daytime winds are more effectively channeled parallel to the valley axis. Although thermally driven winds are not dominant in the Tennessee Valley, a discernible pattern of upvalley daytime winds and downvalley nighttime winds is observed in the tower measurements. Nighttime drainage Rows are particularly evident in the bottomlands between the corrugations. Climatologically, the transition from typical nighttime to typical daytime Row conditions occurs around 0900-1100 LST, and the transition back to nighttime conditions occurs around 1700-1900 LST.Separate sets of numerical simulations were performed for typical summer and winter conditions. These sets differed in their temperature and humidity profiles, surface vegetation characteristics, and soil water. Little systematic difference is observed in the two sets of simulations, suggesting that seasonal variations in surface properties play a relatively minor role in the observed channeling. Overall, the wind channeling can be explained by individually considering the flow deflections caused by the mountain ranges on each side of the valley. Each of these ranges can produce leftward deflections of the oncoming flow depending on its bulk Rossby and Froude numbers. The two ranges appear to interact in that the range on the windward side of the valley tends to reduce the Rossby and Froude numbers of the leeward range, thus allowing the leeward range to be more effective in deflecting the oncoming flow.

A photogrammetric method is described for obtaining estimates of the horizontal diffusion parameter sigma(y) from oblique aerial photographs of smoke clouds. The method requires three reference markers on the ground to determine the geometry in each oblique photograph. Besides the distances between these markers, the only other independent information required for the method is the focal length of the camera lens and the enlargement factor of the photographs. The method is particularly useful for estimating sigma(y) at small sampling times, including relative diffusion. Additionally, it provides high spatial resolution in the downwind and crosswind directions and places no restrictions on the wind directions for which diffusion data can be collected.