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Monthly Weather Review
Article
License: CC BY
Data sources: UnpayWall
Monthly Weather Review
Article . 2010 . Peer-reviewed
Data sources: Crossref
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Simulating the IHOP_2002 Fair-Weather CBL with the WRF-ARW–Noah Modeling System. Part I: Surface Fluxes and CBL Structure and Evolution along the Eastern Track

Authors: Margaret A. Lemone (10063906); Fei Chen (13690); Mukul Tewari (10063909); Jimy Dudhia (5998672); Bart Geerts (5004176); Qun Miao (10063912); Richard L. Coulter (10063915); +1 Authors

Simulating the IHOP_2002 Fair-Weather CBL with the WRF-ARW–Noah Modeling System. Part I: Surface Fluxes and CBL Structure and Evolution along the Eastern Track

Abstract

AbstractFair-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.

Countries
China (People's Republic of), China (People's Republic of), China (People's Republic of), United States
Keywords

Sensible heat flux, Weather Research and Forecasting models, Clear sky, Filter length, Meteorological condition, Moisture fluxes, Vegetation type, atmospheric modeling, Horizontal variation, 551, Flight track, Surface measurement, Atmospheric Sciences, Weather forecasting, Straight lines, Engineering, Clouds, atmospheric structure, Land surface models, Modeling systems, Southeast Kansas, Flight simulators, Vegetation, Convective boundary layers, Spatial filterings, Surface structure, Advanced researches, Computer simulation, Surface influences, convective boundary layer, Weather data, latent heat flux, Roughness length, Gain insight, Surface flux, Heat flux, Soil moisture, Available energy, Horizontal variability, data processing, Metal recovery, cumulus

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
25
Top 10%
Top 10%
Top 10%
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