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Amir Givati, Barry Lynn, Yubao Liu, and Alon Rimmer

Abstract

The Weather Research and Forecasting (WRF) model was employed to provide precipitation forecasts during the 2008/09 and 2009/10 winters (wet season) for Israel and the surrounding region where complex terrain dominates. The WRF precipitation prediction has been coupled with the Hydrological Model for Karst Environment (HYMKE) to forecast the upper Jordan River streamflow. The daily WRF precipitation forecasts were verified against the measurements from a dense network of rain gauges in northern and central Israel, and the simulation results using the high-resolution WRF indicated good agreement with the actual measurements. The daily precipitation amount calculated by WRF at rain gauges located in the upper parts of the Jordan River basin showed good agreement with the actual measurements. Numerical experiments were carried out to test the impact of the WRF model resolution and WRF microphysical schemes, to determine an optimal model configuration for this application. Because of orographic forcing in the region, it is necessary to run WRF with a 4–1.3-km grid increment and with sophisticated microphysical schemes that consider liquid water, ice, snow, and graupel to produce quality precipitation predictions. The hydrological modeling system that ingests the high-resolution WRF forecast precipitation produced good results and improved upon the operational streamflow forecast method for the Jordan River that is now in use. The modeling tools presented in this study are used to support the water-resource-assessment process and studies of seasonal hydroclimatic forecasting in this region.

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Yubao Liu, Fei Chen, Thomas Warner, and Jeffrey Basara

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The National Center for Atmospheric Research (NCAR) and the U.S. Army Test and Evaluation Command have developed a multiscale, rapid-cycling, real-time, four-dimensional data-assimilation and forecasting system that has been in operational use at five Army test ranges since 2001. This system was employed to provide operational modeling support for the Joint Urban 2003 (JU2003) Dispersion Experiment, conducted in Oklahoma City, Oklahoma, during July 2003. To better support this mission, modifications were made to the nonlocal boundary layer (BL) parameterization (known as the Medium Range Forecast scheme) of the fifth-generation Pennsylvania State University–NCAR Mesoscale Model, in order to improve BL forecasts. The NCEP–Oregon State University–Air Force–Hydrologic Research Laboratory land surface model was also improved to better represent urban forcing. Verification of the operational model runs and retrospectively simulated cases show 1) a significantly reduced low bias in the forecast surface wind speed and 2) more realistic daytime BL heights. During JU2003, the forecast urban heat island, urban dry bubble, and urban BL height agree reasonably well with observations and conceptual models. An analysis of three-dimensional atmospheric structures, based on model analyses for eight clear-sky days during the field program, reveals some interesting features of the Oklahoma City urban BL, including complex thermally induced circulations and associated convergence/divergence zones, a nocturnal thermal shadow downwind of the urban area, and the reduction of low-level jet wind speeds by more vigorous nocturnal mixing over the city.

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Yujue Liu, Yubao Liu, Domingo Muñoz-Esparza, Fei Hu, Chao Yan, and Shiguang Miao

Abstract

A multiscale modeling study of a real case has been conducted to explore the capability of the large-eddy simulation version of the Weather Research and Forecasting Model (WRF-LES) over Xiaohaituo Mountain (a game zone for the Beijing, China, 2022 Winter Olympic Games). In comparing WRF-LES results with observations collected during the Mountain Terrain Atmospheric Observations and Modeling (MOUNTAOM) field campaign, it is found that at 37-m resolution with LES settings, the model can reasonably capture both large-scale events and microscale atmospheric circulation characteristics. Employing the Shuttle Radar Topography Mission 1 arc s dataset (SRTM1; ~30 m) high-resolution topographic dataset instead of the traditional USGS_30s (~900 m) dataset effectively improves the model capability for reproducing fluctuations and turbulent features of surface winds. Five sensitivity experiments are conducted to investigate the impact of different PBL treatments, including YSU/Shin and Hong (SH) PBL schemes and LES with 1.5-order turbulence kinetic energy closure model (1.5TKE), Smagorinsky (SMAG), and nonlinear backscatter and anisotropy (NBA) subgrid-scale (SGS) stress models. In this case, at gray-zone scales, differences between YSU and SH are negligible. LES outperform two PBL schemes that generate smaller turbulence kinetic energy and increase the model errors for mean wind speed, energy spectra, and probability density functions of velocity. Another key finding is that wind field features in the boundary layer over complex terrain are more sensitive to the choice of SGS models than above the boundary layer. With the increase of model resolution, the effects of the SGS model become more significant, especially for the statistical characteristics of turbulence. Among these three SGS models, NBA has the best performance. Overall, this study demonstrates that WRF-LES is a promising tool for simulating real weather flows over complex terrain.

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Rod Frehlich, Robert Sharman, Francois Vandenberghe, Wei Yu, Yubao Liu, Jason Knievel, and George Jumper

Abstract

Area-averaged estimates of Cn 2 from high-resolution numerical weather prediction (NWP) model output are produced from local estimates of the spatial structure functions of refractive index with corrections for the inherent smoothing and filtering effects of the underlying NWP model. The key assumptions are the existence of a universal statistical description of small-scale turbulence and a locally universal spatial filter for the NWP model variables. Under these assumptions, spatial structure functions of the NWP model variables can be related to the structure functions of the atmospheric variables and extended to the smaller underresolved scales. The shape of the universal spatial filter is determined by comparisons of model structure functions with the climatological spatial structure function determined from an archive of aircraft data collected in the upper troposphere and lower stratosphere. This method of computing Cn 2 has an important advantage over more traditional methods that are based on vertical differences because the structure function–based estimates avoid reference to the turbulence outer length scale. To evaluate the technique, NWP model–derived structure-function estimates of Cn 2 are compared with nighttime profiles of Cn 2 derived from temperature structure-function sensors attached to a rawinsonde (thermosonde) near Holloman Air Force Base in the United States.

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Teddie L. Keller, Stanley B. Trier, William D. Hall, Robert D. Sharman, Mei Xu, and Yubao Liu

Abstract

At 1818 mountain standard time 20 December 2008, a Boeing 737 jetliner encountered significant crosswinds while accelerating for takeoff at the Denver International Airport (DIA), ran off the side of the runway, and burst into flames. Passengers and crew were able to evacuate quickly, and, although there were injuries, there were no fatalities. Winds around the time of the accident were predominantly from the west, with substantial spatial and temporal speed variability across the airport property. Embedded in this mostly westerly flow were intermittent gusts that created strong crosswinds for the north–south runways. According to the report from the National Transportation Safety Board, it was one of these strong gusts that initiated the events that led to the runway excursion and subsequent crash of the aircraft. Numerous aircraft reported significant mountain-wave activity and turbulence over Colorado on the day of the accident. To determine whether wave activity may have contributed to the strong, intermittent gustiness at DIA, a high-resolution multinested numerical simulation was performed using the Clark–Hall model, with a horizontal grid spacing of 250 m in the inner domain. Results from this simulation suggest that the surface gustiness at DIA was associated with undulations in a train of lee waves in a midtropospheric stable layer above the airport, creating regions of higher-velocity air descending toward the surface. In contrast, a simulation with horizontal grid spacing that was similar to that of a state-of-the-art operational forecast model (3 km) did not predict strong winds at DIA.

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Susanne Grossman-Clarke, Yubao Liu, Joseph A. Zehnder, and Jerome D. Fast

Abstract

A modified version of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) was applied to the arid Phoenix, Arizona, metropolitan region. The ability of the model to simulate characteristics of the summertime urban planetary boundary layer (PBL) was tested by comparing model results with observations from two field campaigns conducted in May/June 1998 and June 2001. The modified MM5 included a refined land use/cover classification and updated land use data for Phoenix and bulk approaches of characteristics of the urban surface energy balance. PBL processes were simulated by a version of MM5’s Medium-Range Forecast Model (MRF) scheme that was enhanced by new surface flux and nonlocal mixing approaches. Simulated potential temperature profiles were tested against radiosonde data, indicating that the modified MRF scheme was able to simulate vertical mixing and the evolution and height of the PBL with good accuracy and better than the original MRF scheme except in the late afternoon. During both simulation periods, it is demonstrated that the modified MM5 simulated near-surface air temperatures and wind speeds in the urban area consistently and considerably better than the standard MM5 and that wind direction simulations were improved slightly.

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Susanne Grossman-Clarke, Joseph A. Zehnder, William L. Stefanov, Yubao Liu, and Michael A. Zoldak

Abstract

A refined land cover classification for the arid Phoenix (Arizona) metropolitan area and some simple modifications to the surface energetics were introduced in the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5). The single urban category in the existing 24-category U.S. Geological Survey land cover classification used in MM5 was divided into three classes to account for heterogeneity of urban land cover. Updated land cover data were derived from 1998 Landsat Thematic Mapper satellite images. The composition of the urban land use classes in terms of typical fractions of vegetation and anthropogenic surfaces was determined from ground-truth information, allowing a variety of moisture availability for evaporation by land cover class. Bulk approaches for characteristics of the urban surface energy budget, such as heat storage, the production of anthropogenic heat, and radiation trapping, were introduced in MM5’s Medium Range Forecast boundary layer scheme and slab land surface model. A 72-h simulation was performed with MM5 on a 2 km × 2 km grid during June 1998. The new land cover classification had a significant impact on the turbulent heat fluxes and the evolution of the boundary layer and improved the capability of MM5 to simulate the daytime part of the diurnal temperature cycle in the urban area. The nighttime near-surface air temperatures were improved significantly by adding radiation trapping, heat storage, and anthropogenic heating to the model.

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Andrea N. Hahmann, Dorita Rostkier-Edelstein, Thomas T. Warner, Francois Vandenberghe, Yubao Liu, Richard Babarsky, and Scott P. Swerdlin

Abstract

The use of a mesoscale model–based four-dimensional data assimilation (FDDA) system for generating mesoscale climatographies is demonstrated. This dynamical downscaling method utilizes the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5), wherein Newtonian relaxation terms in the prognostic equations continually nudge the model solution toward surface and upper-air observations. When applied to a mesoscale climatography, the system is called Climate-FDDA (CFDDA). Here, the CFDDA system is used for downscaling eastern Mediterranean climatographies for January and July. The downscaling method performance is verified by using independent observations of monthly rainfall, Quick Scatterometer (QuikSCAT) ocean-surface winds, gauge rainfall, and hourly winds from near-coastal towers. The focus is on the CFDDA system’s ability to represent the frequency distributions of atmospheric states in addition to time means. The verification of the monthly rainfall climatography shows that CFDDA captures most of the observed spatial and interannual variability, although the model tends to underestimate rainfall amounts over the sea. The frequency distributions of daily rainfall are also accurately diagnosed for various regions of the Levant, except that very light rainfall days and heavy precipitation amounts are overestimated over Lebanon. The verification of the CFDDA against QuikSCAT ocean winds illustrates an excellent general correspondence between observed and modeled winds, although the CFDDA speeds are slightly lower than those observed. Over land, CFDDA- and the ECMWF-derived wind climatographies when compared with mast observations show similar errors related to their inability to properly represent the local orography and coastline. However, the diurnal variability of the winds is better estimated by CFDDA because of its higher horizontal resolution.

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Robert D. Sharman, Yubao Liu, Rong-Shyang Sheu, Thomas T. Warner, Daran L. Rife, James F. Bowers, Charles A. Clough, and Edward E. Ellison

Abstract

Output from the Army Test and Evaluation Command’s Four-Dimensional Weather System’s mesoscale model is used to drive secondary-applications models to produce forecasts of quantities of importance for daily decision making at U.S. Army test ranges. Examples of three specific applications—a sound propagation model, a missile trajectory model, and a transport and diffusion model—are given, along with accuracy assessments using cases in which observational data are available for verification. Ensembles of application model forecasts are used to derive probabilities of exceedance of quantities that can be used to help range test directors to make test go–no-go decisions. The ensembles can be based on multiple meteorological forecast runs or on spatial ensembles derived from different soundings extracted from a single meteorological forecast. In most cases, the accuracies of the secondary-application forecasts are sufficient to meet operational needs at the test ranges.

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Yubao Liu, Thomas T. Warner, Elford G. Astling, James F. Bowers, Christopher A. Davis, Scott F. Halvorson, Daran L. Rife, Rong-Shyang Sheu, Scott P. Swerdlin, and Mei Xu

Abstract

This study builds upon previous efforts to document the performance of the U.S. Army Test and Evaluation Command’s Four-Dimensional Weather Modeling System using conventional metrics. Winds, temperature, and specific humidity were verified for almost 15 000 forecasts at five U.S. Army test ranges using near-surface mesonet data. The primary objective was to use conventional metrics to characterize the degree to which forecast accuracy varies from range to range, within the diurnal cycle, with elapsed forecast time, and among the seasons. It was found that there are large interrange differences in forecast error, with larger errors typically associated with the ranges located near complex orography. Similarly, significant variations in accuracy were noted for different times in the diurnal cycle, but the diurnal dependency varied greatly among the ranges. Factor of 2 differences in accuracy were also found across the seasons.

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