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Edward G. Patton, Peter P. Sullivan, Branko Kosović, Jimy Dudhia, Larry Mahrt, Mark Žagar, and Tomislav Marić

Abstract

A combination of turbulence-resolving large-eddy simulations and observations are used to examine the influence of swell amplitude and swell propagation angle on surface drag. Based on the analysis a new surface roughness parameterization with nonequilibrium wave effects is proposed. The surface roughness accounts for swell amplitude and wavelength and its relative motion with respect to the mean wind direction. The proposed parameterization is tested in uncoupled three-dimensional Weather and Research Forecasting (WRF) simulations at grid sizes near 1 km where we explore potential implications of our modifications for two-way coupled atmosphere–wave models. Wind–wave misalignment likely explains the large scatter in observed nondimensional surface roughness under swell-dominated conditions. Andreas et al.’s relationship between friction velocity and the 10-m wind speed under predicts the increased drag produced by misaligned winds and waves. Incorporating wave-state (speed and direction) influences in parameterizations improves predictive skill. In a broad sense, these results suggest that one needs information on winds and wave state to upscale buoy measurements.

Open access
Xabier Pedruzo-Bagazgoitia, Pedro A. Jiménez, Jimy Dudhia, and Jordi Vilà-Guerau de Arellano

Abstract

This study presents a systematic analysis of convective parameterizations performance with interactive radiation, microphysics, and surface on an idealized day with shallow convection. To this end, we analyze a suite of mesoscale numerical experiments (i.e., with parameterized turbulence). In the first set, two different convection schemes represent shallow convection at a 9-km resolution. These experiments are then compared with model results omitting convective parameterizations at 9- and 3-km horizontal resolution (gray zone). Relevant in our approach is to compare the results against two simulations by different large-eddy simulation (LES) models. Results show that the mesoscale experiments, including the 3-km resolution, are unable to adequately represent the timing, intensity, height, and extension of the shallow cumulus field. The main differences with LES experiments are the following: a too late onset, too high cloud base, and a too early transport of moisture too high, overestimating the second cloud layer. Related to this, both convective parameterizations produce warm and dry biases of up to 2 K and 2 g kg−1, respectively, in the cloud layer. This misrepresentation of the cloud dynamics leads to overestimated shortwave radiation variability, both spacewise and timewise. Domain-averaged shortwave radiation at the surface, however, compares satisfactorily with LES. The shortwave direct and diffuse partition is misrepresented by the convective parameterizations with an underestimation (overestimation) of diffuse (direct) radiation both locally and, by a relative 40% (10%), of the domain average.

Open access
Barry H. Lynn, Alexander P. Khain, Jimy Dudhia, Daniel Rosenfeld, Andrei Pokrovsky, and Axel Seifert

Abstract

Considerable research investments have been made to improve the accuracy of forecasting precipitation systems in cloud-resolving, mesoscale atmospheric models. Yet, despite a significant improvement in model grid resolution and a decrease in initial condition uncertainty, the accurate prediction of precipitation amount and distribution still remains a difficult problem. Now, the development of a fast version of spectral (bin) microphysics (SBM Fast) offers significant potential for improving the description of precipitation-forming processes in mesoscale atmospheric models.

The SBM Fast is based on solving a system of equations for size distribution functions for water drops and three types of ice crystals (plates, columns, and dendrites), as well as snowflakes, graupel, and hail/frozen drops. Ice processes are represented by three size distributions, instead of six in the original SBM code. The SBM uses first principles to simulate microphysical processes such as diffusional growth and collision. A budget for aerosols is used to obtain the spectrum of condensation nuclei, which is used to obtain the initial drop spectrum. Hence, SBM allows one to take into account aerosol effects on precipitation, and corresponding cloud effects on the atmospheric aerosol concentration and distribution. SBM Fast has been coupled with the three-dimensional fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5), which allows SBM Fast to simulate microphysics within a realistic, time-varying mesoscale environment.

This paper describes the first three-dimensional SBM mesoscale model and presents results using 1-km resolution to simulate initial development of a cloud system over Florida on 27 July 1991. The focus is on initial cloud development along the west coast, just prior to sea-breeze formation. The results indicate that the aerosol concentration had a very important impact on cloud dynamics, microphysics, and rainfall.

Vertical cross sections of clouds obtained using SBM Fast are compared to those from a version of the “Reisner2” bulk-parameterization scheme that uses the Kessler autoconversion formula. The results show that this version of “Reisner2” produced vertically upright clouds that progressed very quickly from initial cloud formation to raindrop formation. In contrast, clouds obtained using SBM were relatively long lasting with greater production of stratiform clouds.

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Song-You Hong, Kyo-Sun Sunny Lim, Ju-Hye Kim, Jeong-Ock Jade Lim, and Jimy Dudhia

Abstract

This study examines the relative importance of ice-phase microphysics and sedimentation velocity for hydrometeors in bulk microphysics schemes. The two bulk microphysics schemes having the same number of prognostic water substances, the Weather Research and Forecasting (WRF) Single-Moment 6-Class Microphysics Scheme (WSM6) and the Purdue–Lin scheme (PLIN), are evaluated for a 2D idealized storm case and for a 3D heavy rainfall event over Korea. The relative importance of microphysics and sedimentation velocity for ice particles is illuminated by the additional experiments that exchange the sedimentation velocity formula for graupel in the two schemes. In a 2D idealized storm simulation test bed, it is found that, relative to the PLIN scheme, the WSM6 scheme develops the storm late with weakened intensity because of a slower sedimentation velocity for graupel. Such a weakened intensity of precipitation also appears in a 3D model framework when the WSM6 scheme is used, in conjunction with the overall distribution of the precipitation band southward toward what was observed. The major reason is found to be the ice-phase microphysics of the WSM6 and related ice-cloud–radiation feedback, rather than the smaller terminal velocity for graupel in the WSM6 than in the PLIN scheme.

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Anna C. Fitch, Joseph B. Olson, Julie K. Lundquist, Jimy Dudhia, Alok K. Gupta, John Michalakes, and Idar Barstad

Abstract

A new wind farm parameterization has been developed for the mesoscale numerical weather prediction model, the Weather Research and Forecasting model (WRF). The effects of wind turbines are represented by imposing a momentum sink on the mean flow; transferring kinetic energy into electricity and turbulent kinetic energy (TKE). The parameterization improves upon previous models, basing the atmospheric drag of turbines on the thrust coefficient of a modern commercial turbine. In addition, the source of TKE varies with wind speed, reflecting the amount of energy extracted from the atmosphere by the turbines that does not produce electrical energy.

Analyses of idealized simulations of a large offshore wind farm are presented to highlight the perturbation induced by the wind farm and its interaction with the atmospheric boundary layer (BL). A wind speed deficit extended throughout the depth of the neutral boundary layer, above and downstream from the farm, with a long wake of 60-km e-folding distance. Within the farm the wind speed deficit reached a maximum reduction of 16%. A maximum increase of TKE, by nearly a factor of 7, was located within the farm. The increase in TKE extended to the top of the BL above the farm due to vertical transport and wind shear, significantly enhancing turbulent momentum fluxes. The TKE increased by a factor of 2 near the surface within the farm. Near-surface winds accelerated by up to 11%. These results are consistent with the few results available from observations and large-eddy simulations, indicating this parameterization provides a reasonable means of exploring potential downwind impacts of large wind farms.

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Pedro A. Jiménez, Jimy Dudhia, J. Fidel González-Rouco, Jorge Navarro, Juan P. Montávez, and Elena García-Bustamante

Abstract

This study summarizes the revision performed on the surface layer formulation of the Weather Research and Forecasting (WRF) model. A first set of modifications are introduced to provide more suitable similarity functions to simulate the surface layer evolution under strong stable/unstable conditions. A second set of changes are incorporated to reduce or suppress the limits that are imposed on certain variables in order to avoid undesired effects (e.g., a lower limit in u *). The changes introduced lead to a more consistent surface layer formulation that covers the full range of atmospheric stabilities. The turbulent fluxes are more (less) efficient during the day (night) in the revised scheme and produce a sharper afternoon transition that shows the largest impacts in the planetary boundary layer meteorological variables. The most important impacts in the near-surface diagnostic variables are analyzed and compared with observations from a mesoscale network.

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Greg M. McFarquhar, Henian Zhang, Gerald Heymsfield, Jeffrey B. Halverson, Robbie Hood, Jimy Dudhia, and Frank Marks Jr.

Abstract

Fine-resolution simulations of Hurricane Erin are conducted using the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) to investigate roles of thermodynamic, boundary layer, and microphysical processes on Erin’s structure and evolution. Choice of boundary layer scheme has the biggest impact on simulations, with the minimum surface pressure (P min) averaged over the last 18 h (when Erin is relatively mature) varying by over 20 hPa. Over the same period, coefficients used to describe graupel fall speeds (Vg) affect P min by up to 7 hPa, almost equivalent to the maximum 9-hPa difference between microphysical parameterization schemes; faster Vg and schemes with more hydrometeor categories generally give lower P min. Compared to radar reflectivity factor (Z) observed by the NOAA P-3 lower fuselage radar and the NASA ER-2 Doppler radar (EDOP) in Erin, all simulations overpredict the normalized frequency of occurrence of Z larger than 40 dBZ and underpredict that between 20 and 40 dBZ near the surface; simulations overpredict Z larger than 25 to 30 dBZ and underpredict that between 15 and 25 or 30 dBZ near the melting layer, the upper limit depending on altitude. Brightness temperatures (Tb) computed from modeled fields at 37.1- and 85.5-GHz channels that respond to scattering by graupel-size ice show enhanced scattering, mainly due to graupel, compared to observations. Simulated graupel mixing ratios are about 10 times larger than values observed in other hurricanes. For the control run at 6.5 km averaged over the last 18 simulated hours, Doppler velocities computed from modeled fields (V dop) greater than 5 m s−1 make up 12% of Erin’s simulated area for the base simulation but less than 2% of the observed area. In the eyewall, 5% of model updrafts above 9 km are stronger than 10 m s−1, whereas statistics from other hurricanes show that 5% of updrafts are stronger than only 5 m s−1. Variations in distributions of Z, vertical motion, and graupel mixing ratios between schemes are not sufficient to explain systematic offsets between observations and models. A new iterative condensation scheme, used with the Reisner mixed-phase microphysics scheme, limits unphysical increases of equivalent potential temperature associated with many condensation schemes and reduces the frequency of Z larger than 50 dBZ, but has minimal effect on Z below 50 dBZ, which represent 95% of the modeled hurricane rain area. However, the new scheme changes the Erin simulations in that 95% of the updrafts are weaker than 5 m s−1 and P min is up to 12 hPa higher over the last 18 simulated hours.

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Margaret A. LeMone, Fei Chen, Mukul Tewari, Jimy Dudhia, Bart Geerts, Qun Miao, Richard L. Coulter, and Robert L. Grossman

Abstract

Fair-weather data from the May–June 2002 International H2O Project (IHOP_2002) 46-km eastern flight track in southeast Kansas are compared to simulations using the advanced research version of the Weather Research and Forecasting model coupled to the Noah land surface model (LSM), to gain insight into how the surface influences convective boundary layer (CBL) fluxes and structure, and to evaluate the success of the modeling system in representing CBL structure and evolution. This offers a unique look at the capability of the model on scales the length of the flight track (46 km) and smaller under relatively uncomplicated meteorological conditions.

It is found that the modeled sensible heat flux H is significantly larger than observed, while the latent heat flux (LE) is much closer to observations. The slope of the best-fit line ΔLE/ΔH to a plot of LE as a function of H, an indicator of horizontal variation in available energy H + LE, for the data along the flight track, was shallower than observed. In a previous study of the IHOP_2002 western track, similar results were explained by too small a value of the parameter C in the Zilitinkevich equation used in the Noah LSM to compute the roughness length for heat and moisture flux from the roughness length for momentum, which is supplied in an input table; evidence is presented that this is true for the eastern track as well. The horizontal variability in modeled fluxes follows the soil moisture pattern rather than vegetation type, as is observed; because the input land use map does not capture the observed variation in vegetation. The observed westward rise in CBL depth is successfully modeled for 3 of the 4 days, but the actual depths are too high, largely because modeled H is too high. The model reproduces the timing of observed cumulus cloudiness for 3 of the 4 days.

Modeled clouds lead to departures from the typical clear-sky straight line relating surface H to LE for a given model time, making them easy to detect. With spatial filtering, a straight slope line can be recovered. Similarly, larger filter lengths are needed to produce a stable slope for observed fluxes when there are clouds than for clear skies.

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Margaret A. LeMone, Fei Chen, Mukul Tewari, Jimy Dudhia, Bart Geerts, Qun Miao, Richard L. Coulter, and Robert L. Grossman

Abstract

Fair-weather data along the May–June 2002 International H2O Project (IHOP_2002) eastern track and the nearby Argonne Boundary Layer Experiments (ABLE) facility in southeast Kansas are compared to numerical simulations to gain insight into how the surface influences convective boundary layer (CBL) structure, and to evaluate the success of the modeling system in replicating the observed behavior. Simulations are conducted for 4 days, using the Advanced Research version of the Weather Research and Forecasting (WRF) model coupled to the Noah land surface model (LSM), initialized using the High-Resolution Land Data Assimilation System (HRLDAS). Because the observations focus on phenomena less than 60 km in scale, the model is run with 1-km grid spacing, offering a critical look at high-resolution model behavior in an environment uncomplicated by precipitation.

The model replicates the type of CBL structure on scales from a few kilometers to ∼100 km, but some features at the kilometer scales depend on the grid spacing. Mesoscale (tens of kilometers) circulations were clearly evident on 2 of the 4 days (30 May and 20 June), clearly not evident on 1 day (22 June), with the situation for the fourth day (17 June) ambiguous. Both observed and modeled surface-heterogeneity-generated mesoscale circulations are evident for 30 May. On the other hand, 20 June satellite images show north-northwest–south-southeast cloud streets (rolls) modulated longitudinally, presumably by tropospheric gravity waves oriented normal to the roll axis, creating northeast–southwest ridges and valleys spaced 50–100 km apart. Modeled cloud streets showed similar longitudinal modulation, with the associated two-dimensional structure having maximum amplitude above the CBL and no relationship to the CBL temperature distribution; although there were patches of mesoscale vertical velocity correlated with CBL temperature. On 22 June, convective rolls were the dominant structure in both model and observations.

For the 3 days for which satellite images show cloud streets, WRF produces rolls with the right orientation and wavelength, which grows with CBL depth. Modeled roll structures appeared for the range of CBL depth to Obukhov length ratios (−zi/L) associated with rolls. However, sensitivity tests show that the roll wavelength is also related to the grid spacing, and the modeled convection becomes more cellular with smaller grid spacing.

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Ethan D. Gutmann, Roy M. Rasmussen, Changhai Liu, Kyoko Ikeda, David J. Gochis, Martyn P. Clark, Jimy Dudhia, and Gregory Thompson

Abstract

Statistical downscaling is widely used to improve spatial and/or temporal distributions of meteorological variables from regional and global climate models. This downscaling is important because climate models are spatially coarse (50–200 km) and often misrepresent extremes in important meteorological variables, such as temperature and precipitation. However, these downscaling methods rely on current estimates of the spatial distributions of these variables and largely assume that the small-scale spatial distribution will not change significantly in a modified climate. In this study the authors compare data typically used to derive spatial distributions of precipitation [Parameter-Elevation Regressions on Independent Slopes Model (PRISM)] to a high-resolution (2 km) weather model [Weather Research and Forecasting model (WRF)] under the current climate in the mountains of Colorado. It is shown that there are regions of significant difference in November–May precipitation totals (>300 mm) between the two, and possible causes for these differences are discussed. A simple statistical downscaling is then presented that is based on the 2-km WRF data applied to a series of regional climate models [North American Regional Climate Change Assessment Program (NARCCAP)], and the downscaled precipitation data are validated with observations at 65 snow telemetry (SNOTEL) sites throughout Colorado for the winter seasons from 1988 to 2000. The authors also compare statistically downscaled precipitation from a 36-km model under an imposed warming scenario with dynamically downscaled data from a 2-km model using the same forcing data. Although the statistical downscaling improved the domain-average precipitation relative to the original 36-km model, the changes in the spatial pattern of precipitation did not match the changes in the dynamically downscaled 2-km model. This study illustrates some of the uncertainties in applying statistical downscaling to future climate.

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