Abstract

Model improvement efforts involve an evaluation of changes in model skill in response to changes in model physics and parameterization. When using wind measurements from various remote sensors to determine model forecast accuracy, it is important to understand the effects of measurement-uncertainty differences among the sensors resulting from differences in the methods of measurement, the vertical and temporal resolution of the measurements, and the spatial variability of these differences. Here we quantify instrument measurement variability in 80-m wind speed during WFIP2 and its impact on the calculated errors and the change in error from one model version to another. The model versions tested involved updates in model physics from HRRRv1 to HRRRv4, and reductions in grid interval from 3 km to 750 m. Model errors were found to be 2–3 m s⁻¹. Differences in errors as determined by various instruments at each site amounted to about 10% of this value, or 0.2–0.3 m s⁻¹. Changes in model skill due to physics or grid-resolution updates also differed depending on the instrument used to determine the errors; most of the instrument-to-instrument differences were ∼0.1 m s⁻¹, but some reached 0.3 m s⁻¹. All instruments at a given site mostly showed consistency in the sign of the change in error. In two examples, though, the sign changed, illustrating a consequence of differences in measurements: errors determined using one instrument may show improvement in model skill, whereas errors determined using another instrument may indicate degradation. This possibility underscores the importance of having accurate measurements to determine the model error.

Abstract

From 2014 to 2017, two Department of Energy buoys equipped with Doppler lidar were deployed off the U.S. East Coast to provide long-term measurements of hub-height wind speed in the marine environment. We performed simulations of selected cases from the deployment using a 5-km configuration of the Weather Research and Forecasting (WRF) Model, to see if simulated hub-height speeds could produce closer agreement with the observations than existing reanalysis products. For each case we performed two additional simulations: one in which marine surface roughness height was one-way coupled to forecast wave parameters from a stand-alone WaveWatch III (WW3) simulation, and another in which WRF and WW3 were two-way coupled using the Coupled Ocean–Atmosphere–Wave–Sediment–Transport (COAWST) framework. It was found that all the 5-km WRF simulations improved 90-m wind speed statistics for the tropical cyclone case of 8 May 2015 and the cold frontal case of 25 March 2016, but not the nor’easter of 18 January 2016. The impact of wave coupling on buoy-level (4 m) wind speed was modest and case dependent, but when present, the impact was typically seen at 90 m as well, being as large as 10% in stable conditions. One-way wave coupling consistently reduced wind speeds, improving biases for 25 March 2016 but worsening them for 8 May 2015. Two-way wave coupling mitigated these negative biases, improved wave field representation and statistics, and mostly improved 4-m wind field correlation coefficients, at least at the Virginia buoy, largely due to greater self-consistency between wind and wave fields.

Abstract

A detailed understanding of interactions of aerosols, cloud droplets/ice crystals, and trace gases within the atmosphere is of prime importance for an accurate understanding of Earth’s weather and climate. One aspect that remains especially vexing is that clouds are ubiquitously turbulent, and therefore thermodynamic and compositional variables, such as water vapor supersaturation, fluctuate in space and time. With these problems in mind, a multiphase, turbulent reaction chamber—called the Π chamber because of the internal volume of 3.14 m³ with the cylindrical insert installed—has been developed. It is capable of pressures ranging from 1,000 to –60 hPa and can sustain temperatures of –55° to 55°C, thereby spanning much of the range of tropospheric clouds. To control the relative humidity in the chamber, it can be operated with a stable, unstable, or neutral temperature difference between the top and bottom surfaces, with or without expansion. A negative temperature difference induces turbulent Rayleigh–Bénard convection and associated supersaturation generation through isobaric mixing. Supporting instrumentation includes a suite of aerosol generation and characterization techniques; temperature, pressure, and humidity sensors; and a phase Doppler interferometer. Initial characterization experiments demonstrate the ability to sustain steady-state turbulent cloud conditions for times greater than 1 day, with droplet diameters typically in the range of 5–40 µm. Typical turbulence has root-mean-square velocity fluctuations on the order of 10 cm s^–1 and kinetic energy dissipation rates of 1 × 10^–3 W kg^–1.

Abstract

A Doppler lidar deployed to the center of the Great Salt Lake (GSL) basin during the Vertical Transport and Mixing (VTMX) field campaign in October 2000 found a diurnal cycle of the along-basin winds with northerly up-basin flow during the day and a southerly down-basin low-level jet at night. The emphasis of VTMX was on stable atmospheric processes in the cold-air pool that formed in the basin at night. During the night the jet was fully formed as it entered the GSL basin from the south. Thus, it was a feature of the complex string of basins draining toward the Great Salt Lake, which included at least the Utah Lake basin to the south. The timing of the evening reversal to down-basin flow was sensitive to the larger-scale north–south pressure gradient imposed on the basin complex. On nights when the pressure gradient was not too strong, local drainage flow (slope flows and canyon outflow) was well developed along the Wasatch Range to the east and coexisted with the basin jet. The coexistence of these two types of flow generated localized regions of convergence and divergence, in which regions of vertical motion and transport were focused. Mesoscale numerical simulations captured these features and indicated that updrafts on the order of 5 cm s⁻¹ could persist in these localized convergence zones, contributing to vertical displacement of air masses within the basin cold pool.

From 6 January to 28 February 1993, the second phase of the Pilot Radiation Observation Experiment (PROBE) was conducted in Kavieng, Papua New Guinea. Routine data taken during PROBE included radiosondes released every 6 h and 915-MHz Wind Profiler–Radio Acoustic Sounding System (RASS) observations of winds and temperatures. In addition, a dual-channel Microwave Water Substance Radiometer (MWSR) at 23.87 and 31.65 GHz and a Fourier Transform Infrared Radiometer (FTIR) were operated. The FTIR operated between 500 and 2000 cm⁻¹ and measured some of the first high spectral resolution (1 cm⁻¹) radiation data taken in the Tropics. The microwave radiometer provided continuous measurements within 30-s resolution of precipitable water vapor (PWV) and integrated cloud liquid, while the RASS measured virtual temperature profiles every 30 min. In addition, occasional lidar soundings of cloud-base heights were available. The MWSR and FTIR data taken during PROBE were compared with radiosonde data. Significant differences were noted between the MWSR and the radiosonde observations of PWV. The probability distribution of cloud liquid water was derived and is consistent with a lognormal distribution. During conditions that the MWSR did not indicate the presence of cloud liquid water, broadband long- and shortwave irradiance data were used to identify the presence of cirrus clouds or to confirm the presence of clear conditions. Comparisons are presented between measured and calculated radiance during clear conditions, using radiosonde data as input to a line-by-line Radiative Transfer Model. A case study is given of a drying event in which the PWV dropped from about 5.5 cm to a low of 3.8 cm during a 24-h period. The observations during the drying event are interpreted using PWV images obtained from data from the Defense Meteorological Satellite Program/Special Sensor Microwave/Imager and of horizontal flow measured by the wind profiler. The broadband irradiance data and the RASS soundings were also examined during the drying event.

Abstract

Continuous estimates of the oceanic meridional heat transport in the Atlantic are derived from the Rapid Climate Change–Meridional Overturning Circulation (MOC) and Heatflux Array (RAPID–MOCHA) observing system deployed along 26.5°N, for the period from April 2004 to October 2007. The basinwide meridional heat transport (MHT) is derived by combining temperature transports (relative to a common reference) from 1) the Gulf Stream in the Straits of Florida; 2) the western boundary region offshore of Abaco, Bahamas; 3) the Ekman layer [derived from Quick Scatterometer (QuikSCAT) wind stresses]; and 4) the interior ocean monitored by “endpoint” dynamic height moorings. The interior eddy heat transport arising from spatial covariance of the velocity and temperature fields is estimated independently from repeat hydrographic and expendable bathythermograph (XBT) sections and can also be approximated by the array.

The results for the 3.5 yr of data thus far available show a mean MHT of 1.33 ± 0.40 PW for 10-day-averaged estimates, on which time scale a basinwide mass balance can be reasonably assumed. The associated MOC strength and variability is 18.5 ± 4.9 Sv (1 Sv ≡ 10⁶ m³ s⁻¹). The continuous heat transport estimates range from a minimum of 0.2 to a maximum of 2.5 PW, with approximately half of the variance caused by Ekman transport changes and half caused by changes in the geostrophic circulation. The data suggest a seasonal cycle of the MHT with a maximum in summer (July–September) and minimum in late winter (March–April), with an annual range of 0.6 PW. A breakdown of the MHT into “overturning” and “gyre” components shows that the overturning component carries 88% of the total heat transport. The overall uncertainty of the annual mean MHT for the 3.5-yr record is 0.14 PW or about 10% of the mean value.

Abstract

Complex-terrain locations often have repeatable near-surface wind patterns, such as synoptic gap flows and local thermally forced flows. An example is the Columbia River Valley in east-central Oregon–Washington, a significant wind energy generation region and the site of the Second Wind Forecast Improvement Project (WFIP2). Data from three Doppler lidars deployed during WFIP2 define and characterize summertime wind regimes and their large-scale contexts, and provide insight into NWP model errors by examining differences in the ability of a model [NOAA’s High-Resolution Rapid Refresh (HRRR version 1)] to forecast wind speed profiles for different flow regimes. Seven regimes were identified based on daily time series of the lidar-measured rotor-layer winds, which then suggested two broad categories. First, in three of the regimes the primary dynamic forcing was the large-scale pressure gradient. Second, in two other regimes the dominant forcing was the diurnal heating-cooling cycle (regional sea-breeze-type dynamics), including the marine intrusion previously described, which generates strong nocturnal winds over the region. For the large-scale pressure gradient regimes, HRRR had wind speed biases of ~1 m s⁻¹ and RMSEs of 2–3 m s⁻¹. Errors were much larger for the thermally forced regimes, owing to the premature demise of the strong nocturnal flow in HRRR. Thus, the more dominant the role of surface heating in generating the flow, the larger the errors. Major errors could result from surface heating of the atmosphere, boundary layer responses to that heating, and associated terrain interactions. Measurement/modeling research programs should be designed to determine which of these modeled processes produce the largest errors, so those processes can be improved and errors reduced.

Abstract

Previous studies of the low-level jet (LLJ) over the central Great Plains of the United States have been unable to determine the role that mesoscale and smaller circulations play in the transport of moisture. To address this issue, two aircraft missions during the International H₂O Project (IHOP_2002) were designed to observe closely a well-developed LLJ over the Great Plains (primarily Oklahoma and Kansas) with multiple observation platforms. In addition to standard operational platforms (most important, radiosondes and profilers) to provide the large-scale setting, dropsondes released from the aircraft at 55-km intervals and a pair of onboard lidar instruments—High Resolution Doppler Lidar (HRDL) for wind and differential absorption lidar (DIAL) for moisture—observed the moisture transport in the LLJ at greater resolution. Using these observations, the authors describe the multiscalar structure of the LLJ and then focus attention on the bulk properties and effects of scales of motion by computing moisture fluxes through cross sections that bracket the LLJ. From these computations, the Reynolds averages within the cross sections can be computed. This allow an estimate to be made of the bulk effect of integrated estimates of the contribution of small-scale (mesoscale to convective scale) circulations to the overall transport. The performance of the Weather Research and Forecasting (WRF) Model in forecasting the intensity and evolution of the LLJ for this case is briefly examined.

Abstract

To assess current capabilities for measuring flow within the atmospheric boundary layer, including within wind farms, the U.S. Department of Energy sponsored the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) campaign at the Boulder Atmospheric Observatory (BAO) in spring 2015. Herein, we summarize the XPIA field experiment, highlight novel measurement approaches, and quantify uncertainties associated with these measurement methods. Line-of-sight velocities measured by scanning lidars and radars exhibit close agreement with tower measurements, despite differences in measurement volumes. Virtual towers of wind measurements, from multiple lidars or radars, also agree well with tower and profiling lidar measurements. Estimates of winds over volumes from scanning lidars and radars are in close agreement, enabling the assessment of spatial variability. Strengths of the radar systems used here include high scan rates, large domain coverage, and availability during most precipitation events, but they struggle at times to provide data during periods with limited atmospheric scatterers. In contrast, for the deployment geometry tested here, the lidars have slower scan rates and less range but provide more data during nonprecipitating atmospheric conditions. Microwave radiometers provide temperature profiles with approximately the same uncertainty as radio acoustic sounding systems (RASS). Using a motion platform, we assess motion-compensation algorithms for lidars to be mounted on offshore platforms. Finally, we highlight cases for validation of mesoscale or large-eddy simulations, providing information on accessing the archived dataset. We conclude that modern remote sensing systems provide a generational improvement in observational capabilities, enabling the resolution of finescale processes critical to understanding inhomogeneous boundary layer flows.