An Evaluation of a Diagnostic Wind Model (CALMET)

Abstract

A U.S. Environmental Protection Agency (EPA)-approved diagnostic wind model [California Meteorological Model (CALMET)] was evaluated during a typical lake-breeze event under fair weather conditions in the Chicago region. The authors focused on the performance of CALMET in terms of simulating winds that were highly variable in space and time. The reference winds were generated by the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5) assimilating system, with which CALMET results were compared. Statistical evaluations were conducted to quantify overall model differences in wind speed and direction over the domain. Below 850 m above the surface, relative differences in (layer averaged) wind speed were about 25%-40% during the simulation period; wind direction differences generally ranged from 6°to 20°. Above 850 m, the differences became larger because of the limited number of upper-air stations near the studied domain. Analyses implied that model differences were dependent on time because of time-dependent spatial variability in winds. Trajectory analyses were made to examine the likely spatial dependence of CALMET deviations from the reference winds within the domain. These analyses suggest that the quality of CALMET winds in local areas depended on their proximity to the lake-breeze front position. Large deviations usually occurred near the front area, where observations cannot resolve the spatial variability of wind, or in the fringe of the domain, where observations are lacking. Results simulated using different datasets and model options were also compared. Differences between CALMET and the reference winds tended to be reduced with data sampled from more stations or from more uniformly distributed stations. Suggestions are offered for further improving or interpreting CALMET results under complex wind conditions in the Chicago region, which may also apply to other regions.

Aircraft wind measurements to assess a coupled WRF‐CALMET mesoscale system

“…These results are basically consistent with Bellasio et al (), who applied CALMET over a 4 km resolution domain in northern Italy after ingestion of a number of surface stations and one tall tower station, and proved the model was not capable of resolving microclimate effects such as lake breezes. It has been well recognized in the literature that CALMET is capable of estimating horizontal wind fields under significant spatial and temporal variability, when ingested observations are enough to resolve characteristic local flows (Wang et al , ). Yim et al () pointed out that CALMET capability in reproducing local wind fields strictly depends on density, frequency and accuracy of the observations used as input.…”

“…However, they have limitations due to simplification in physics, and uncertainty in the initial state, lateral boundary conditions and surface characteristics (Al–Yahyai et al , ). While NWP models are operationally applied for weather forecasts, diagnostic wind models based on mass conservation still play an important role because of their fast computation and high accuracy in local areas (Wang et al , ), where they are capable of considering fine scale details such as, e.g., complex topography and land–water interfaces (Hu et al , ). Examples of diagnostic models are AERMET (US EPA, ), MCSCIPUF (Sykes et al , ), and CALMET (Scire et al , ).…”

Evidence of active or passive downwind dispersal in mark–release–recapture of moths

“…Twice daily, vertical profiles of pressure, elevation, temperature, wind direction, and wind speed for each sounding level were extracted from the New Zealand Climate Database for the nearest upper air meteorological station (36°47′34″S, 174°37′26″E). The wind direction and wind speed data for the duration of each release–recapture period were interpolated onto a 200 × 200 m series of 10‐min grids covering the study area using CALMET modelling software (Scire et al., 1998; Wang et al., 2008).…”

Dynamic Wind Field Simulation and Efficiency Analysis Over 3D Terrain Based on the Lagrangian Method

“…element method widely used. Wang et al [2] discussed the advantages of these algorithms for diagnosing wind fields. In addition, Li et al [3] expounded how these algorithms should be applied to wind fields over complex terrain with CFD.…”