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• Stable PBL
• Interaction between heterogeneous surface and atmosphere
• Interaction between ocean and atmosphere
• Subfilter-scale turbulence in LES

Page 2:

• International H2O Project (IHOP)
• Convective PBL and turbulence dispersion
• Wildfire research

Surface measurements

Related websites:
http://www.rap.ucar.edu/projects/land/IHOP/index.htm
http://www.atd.ucar.edu/dir_off/projects/2002/IHOP.html

LeMone actively participated in the design and siting of the surface flux measurements during IHOP. LeMone, Robert Grossman (Colorado Research Associates), Ken Davis (Pennsylvania State University), and Fei Chen (NCAR/RAP) requested 9 ISFF surface flux stations, to enable further testing of land-surface models, without the deficiencies of the CASES-97 dataset. Peter Blanken (University of Colorado) supplied a 10th surface station, which was maintained by J. Alfieri, his graduate student. The stations were located along three King-Air flight tracks, so that King-Air fluxes could be integrated into the observational dataset to be used for model evaluation. The improved models could then be used to characterize surface fluxes, across the IHOP domain, for numerical modeling studies. The flight tracks were laid out along a roughly east-west line (Fig. 39) to maximize the contrast in precipitation and land cover. The eastern track coincides with the southern-most track used in CASES-97, to enable comparison of the two data sets. The western (radar) track provides data in a semiarid environment, and was located close to the S-Pol radar and the concentrated group of instruments at Homestead. The center track, about halfway between, sampled intermediate conditions. Three of the nine flux stations were assigned to each track, with the 10th station assigned to the western track. As in previous experiments, the stations were located to sample the important land use categories, grassland varying from Conservation Reserve Program ungrazed grass to over-grazed (6 stations), winter wheat (2 stations), sagebrush (1 station), and bare ground (one station).

Figure 39. Locations of the three King Air flight tracks flown during IHOP. The radar track is located close to the "Homestead" site where there were several remote sensing instruments; and east of the S-Pol radar. The eastern track corresponds to the southernmost track used in CASES-97.

The ISFF flux measurements were supplemented with additional soil-moisture measurements, vegetation measurements, and carbon dioxide. In comparisons of three LSMs with CASES-97 surface heat flux data, Chen et al. found the usefulness of the comparisons in suggesting improvements to the LSMs was greatly limited by the lack of soil measurements below 5 cm. Thus, Chen and LeMone obtained funding through the NCAR Water Cycle Initiative to obtain instruments to obtain this important information, which included soil temperature, volumetric soil water content, and soil matric potential down to 1 m below the surface. Richard Cuenca (Oregon State University) chose the instruments, assisted in installation, and determined soil hydraulic conductivity, soil density, and soil texture. Similarly, Chen and Yates (e.g., Yates et al. 2001) found that the vegetation characterization done in CASES-97 -- basically photographs and measurements of canopy height - proved useful in interpretation of observed and modeled sensible and latent heat flux. Thus, investigators decided to include more vegetation characterization measurements in IHOP. The carbon dioxide measurements were made by Scott Richardson (Pennsylvania State University)

After considerable effort by Chen, LeMone, Grossman, and Yates, a suite of instruments was obtained and a protocol was developed for surface characterization by Yates and the students, with help from Tony Delany (NCAR/ATD). The measurements included vegetation and TDR, and gravimetric soil-moisture. The vegetation characterization measurements included NDVI, LAI, canopy temperature, canopy height, photographs, stomatal conductance, and species identification. The NDVI, LAI, temperature, and height measurements were made, along with Trime soil-moisture measurements, at 5-m intervals along 45-m transects, at each of the ten surface flux stations, at week- to 10-day intervals, by three students - Alfieri, Joshua Uebelherr (now a graduate student at Duke), and Heather McIntyre (NCAR/RAP and an undergraduate at Metro State). Dev Niyogi (North Carolina State University) and Alfieri made diurnal stomatal conductance measurements at representative locations.

Aircraft measurements

LeMone, Grossman, Chen and Ken Davis (Pennsylvania State University) used the University of Wyoming King Air to characterize the low level fluxes and boundary layer structure. The first objective was achieved by flying between 7 and 11 flight legs, at 65 m above the surface; the second objective was achieved through repeated straight and level legs, at 3-4 heights, from the surface to just above the boundary layer. Five sorties were flown along each of the flight tracks, under a variety of conditions.

The objective of the flights was to determine the role of the surface characteristics (vegetation cover, soil characteristics, and terrain) in horizontal heterogeneity, in fluxes and structure. Both surface characteristics and horizontal heterogeneity influence storm initiation and evolution. Figure 40 shows that the flight legs were flown over varying terrain, with varying vegetation characteristics. The low NDVI values for the western track indicate sparse vegetation; indeed the surface radiometric temperature, which is closely tied to fluxes, is mainly a function of soil moisture along this track.

Figure 40. Characteristics of the three flight tracks used in IHOP. Left: Western track; Center: center track; Right: Eastern Track. Top frame: relative elevation of terrain beneath the track, 2nd frame: aircraft altitude above the surface. Third frame: Radiometric Surface Temperature. Bottom frame: Normalized Differential Vegetation Index.

Figure 41 illustrates the effect of a strong gradient in soil moisture, due to heavy rains at the southern end of the western track, two days before. Note the radiometric surface temperature ("Heiman") is 15 degrees warmer at the dry north end than the wet south end of the track, and the potential temperature at 60 m above the ground is 1 degree warmer. This warmth extends through the boundary layer, which is deeper over the north end of the track. The air was more moist at the southern end of the track, but the moist patch moved northward with time. In contrast, it is primarily vegetation that determines the surface temperature along the eastern track.

Figure 41. For five flight legs flown at 60 m agl over the western track on 29 May. Left panel: radiometric surface temperature; Center Panel: Potential temperature (K); Right Panel: Mixing ratio g/kg-1

Si-Wan Kim (Seoul National University), Moeng and Weil (CIRES/CU) performed a Lagrangian particle dispersion modeling of fumigation of pollutants in and above the entrainment zone into a growing convective boundary layer. Probability density function of particle locations is calculated from particle trajectories, determined by the resolved scale velocity field from the NCAR large-eddy simulation (LES) model, and by a stochastic subgrid scale velocity field from Weil's refined subgrid scale model. Concentration distribution shows good agreement with the water tank experimental data of Deardorff and Willis (1982), and Hibberd and Luhar (1996), for both slow and fast entrainment cases (Figures 42 and 43). Starting time of fumigation (i.e., the time when some particle reaches the ground level) depends strongly on whether the height of the source is within the entrainment zone or above it. When particles are released within the entrainment zone, the ground-level crosswind-integrated concentration, at a downstream distance close to the source, is well predicted from the Lagrangian model compared to the tank data. However, the particle quantity is overestimated by a Eulerian model (Cai and Luhar, 2002), which may imply an excessive diffusion of the Eulerian model near the source region. Overall, this Lagrangian modeling of particle dispersion, based on the LES generated flow field, shows promising results for the prediction of concentration distribution of materials emitted within and above the entrainment zone, from factory stacks or from an emergency situation.

Figure 42. Near ground level dimensionless crosswind-integrated concentration as a function of time compared to water tank experiments of (a) Deardorff and Willis 1982*, and (b) Hibberd and Luhar 1996**. Symbols stand for laboratory data, and lines for Lagrangian particle dispersion model results. * Deardorff J. W., and Willis G. E. (1982) Ground-level concentrations due to fumigation into an entraining mixed layer. Atmos. Environ. 16, 1159-1170. **Hibberd M. F., and Luhar A. K. (1996) A laboratory study and improved PDF model of fumigation into a growing convective boundary layer. Atmos. Environ. 30, 3633-3649.

Figure 43. Dimensionless crosswind-integrated concentration for slow entrainment case from (a) Lagragian particle dispersion model (we/w* = 0.015) and from (b) Hibberd and Luhar 1996 tank experiment (we/w* = 0.014) and for fast entrainment case from (c) Lagragian particle dispersion model (we/w* = 0.042) and from (d) Hibberd and Luhar 1996 tank experiment (we/w* = 0.038).

Kim, Soon-Ung Park (Seoul National University, Korea), and Moeng have also investigated the entrainment mechanism in a strongly sheared convective boundary layer (CBL) where large entrainment heat flux has been observed. The purpose of this study was to investigate the interaction between the boundary layer and the entrainment zone, which leads to strong entrainment, and to provide new insights into the entrainment parameterization of strongly sheared CBL. Large-eddy simulations of three CBLs were performed with a constant surface heat flux of 0.05 Kms-1 and varying geostrophic wind speeds from 5 ms-1 to 15 ms-1. Heat flux profiles show that the ratio of the entrainment heat flux relative to the surface heat flux decreases from -0.13 to -0.30 with increasing wind shear. The thickness of the entrainment zone, relative to the depth of the well-mixed layer, also increases substantially from 0.36 to 0.73 with increasing wind shear. This implies that the entrainment zone thickness is closely related to the entrainment rate in strongly sheared CBL, and hence, should be included in entrainment-rate parameterization. Concentrated vortices perpendicular to the mean boundary-layer wind direction are identified in the entrainment zone for a strong wind shear case. These vortices are found to develop above the ascending branch of convective rolls, and appear as large-scale wavy motions generated by the Kelvin-Helmholtz (K-H) instability (see Figures 44 and 45). A quadrant analysis of heat flux shows that in the strong wind shear case, large fluctuations of temperature and vertical velocity by K-H instability like wavy motions result in greater heat fluxes at each quadrant than those in the weak wind shear case.

Figure 44. Instantaneous horizontal distributions of (a) vertical velocity at z/h1=0.5, (b) local Richardson number at z/h1=1.0, and (c) indicator of vortex strength, at z/h1=1.0 for the geostrophic wind speed of 15 ms-1 case. h1 is the height of the most negative heat flux, usually called the top of convective boundary layer. Contours are shaded for the positive vertical velocity, for positive Richardson number less than 0.25 and for less than -5.0 ´ 10-5 (s -2).

Figure 45. Evolution of entrainment surfaces for the geostrophic wind speed of 15 ms-1 with the time interval of 100 s. Potential temperature in the entrainment zone (from h0 to h2, h0 and h2 are the bottom and the top of entrainment zone, respectively) is contoured in the X-Z plane. (min, max, interval of contours) are (289.0, 290.8, 0.2) (K).

Janice Coen (joint appointment with RAP), with collaborators Don Latham (U.S. Forest Service) and Terry Clark analyzed coupled atmosphere-fire simulations of a wildland fire to show that the universally-observed "elliptical shape" [Fig. 46] arises from even simple experiments and is a direct consequence of fire-atmosphere interactions. As a modeled fire (see Movie 9) initialized as a line in 3 m/s winds, from the left) evolves (Fig. 47 b-d) it takes on a shape well-recognized in real fires, that of a bow or ellipse of fire surrounding the ignited and burned fuel. The fireline has three regions: 1) the "head" - the fastest moving, leading edge of the fire where heat is focused, 2) two "flanks" along the side where the winds blow almost parallel to the fire line, and 3) the "back" - the slowest moving part of the fire that creeps into the wind. The heat produced by the fire rises in updrafts that the winds focus at the head. These updrafts draw warm air into their base from all directions, guiding the wind to flow along the flanks and focus the heat at the front. This creates a self-perpetuating shape, which interestingly, is observed to be the same in either grass, brush, or forest fires.

	To view the movie, place mouse over image. Alternately, for slower connections, you may use the links below to download the movie. Wildfire movie (animated GIF) Wildfire movie (AVI format)
Movie 9. Volume rendered buoyancy and horizontal wind vectors at 3 m above ground (arrows, shown every 6th gridpoint)) during the evolution of a fire line into the "universal" fire shape (69 min simulation). Domain's dimensions are 2.8 km x 2.8 km x 1.03 km.

Figure 46. This photo from the Onion sagebrush fire in Owens Valley, CA, in 1985 is an example of the frequently observed bowed fireline shape. The "fingers" are about 1 km wide. (Courtesy of U.S. Forest Service)

Figure 47. Plots of three-dimensional buoyancy (volume rendered), two-dimensional shaded contour of buoyancy at 3 m AGL, and horizontal wind vectors at 3 m AGL at 6 times from initialization: a) 0:06 (6 sec), b) 5:24, c) 20:42, d) 1:05:00, e) 1:07:48, and f) 1:08:54 . The domain's dimensions are 2.8 km x 2.8 km x 1.03 km. Vectors are shown every 6th gridpoint.

Although this fire line maintains this somewhat steady shape for an hour of simulation, perturbations occur, and may amplify, due to the inherently nonlinear dynamic processes. A perturbation in the velocity field along the fire line leads to a perturbation in the spread rate into unburned fuel, and consequently, a perturbation in the buoyancy (increasing horizontal vorticity) and updraft (which tilts and stretches the horizontal vorticity), producing a fire whirl. These fire whirls (Fig. 47 e-f) amplify and propagate downwind along the flanks toward the head, where interaction with other whirls may burst forward or break up the overall fire line shape.