Impact of turbulence, land surface, and radiation parameterizations on simulated boundary layer properties in a coastal environment

Zhong, Shiyuan; In, Hee-Jin; Clements, Craig B.

doi:10.1029/2006jd008274

Cited by 40 publications

(34 citation statements)

References 24 publications

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“…Such convection would in turn alter the boundary layer characteristics beyond what was produced directly by the PBL scheme. Likewise, the intensity, timing, and inland penetration of simulated sea breezes are sometimes, but not always, affected by the boundary layer structures generated by different PBL schemes (Miao et al 2009;Zhong et al 2007). While indirect impacts such as these are observable and would contribute to the performance of parameter estimation, they are also likely to be situation specific and, in the case of moist convection, highly nonlinear.…”

Section: Experimental Designmentioning

confidence: 99%

Evaluation of Planetary Boundary Layer Scheme Sensitivities for the Purpose of Parameter Estimation

Nielsen‐Gammon

Zhang

et al. 2010

Monthly Weather Review

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Meteorological model errors caused by imperfect parameterizations generally cannot be overcome simply by optimizing initial and boundary conditions. However, advanced data assimilation methods are capable of extracting significant information about parameterization behavior from the observations, and thus can be used to estimate model parameters while they adjust the model state. Such parameters should be identifiable, meaning that they must have a detectible impact on observable aspects of the model behavior, their individual impacts should be a monotonic function of the parameter values, and the various impacts should be clearly distinguishable from each other.A sensitivity analysis is conducted for the parameters within the Asymmetrical Convective Model, version 2 (ACM2) planetary boundary layer (PBL) scheme in the Weather Research and Forecasting model in order to determine the parameters most suited for estimation. A total of 10 candidate parameters are selected from what is, in general, an infinite number of parameters, most being implicit or hidden. Multiple sets of model simulations are performed to test the sensitivity of the simulations to these 10 particular ACM2 parameters within their plausible physical bounds. The most identifiable parameters are found to govern the vertical profile of local mixing within the unstable PBL, the minimum allowable diffusivity, the definition of the height of the unstable PBL, and the Richardson number criterion used to determine the onset of turbulent mixing in stable stratification. Differences in observability imply that the specific choice of parameters to be estimated should depend upon the characteristics of the observations being assimilated.

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Section: Experimental Designmentioning

confidence: 99%

Evaluation of Planetary Boundary Layer Scheme Sensitivities for the Purpose of Parameter Estimation

Nielsen‐Gammon

Zhang

et al. 2010

Monthly Weather Review

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“…The UBL depth is a key variable that describes the boundary-layer structure, and in many applications such as air-pollution prediction and weather forecasting (Beyrich 1997;Miao et al 2011;Barlage et al 2016). As for air-quality prediction, small errors in PBL depth can significantly degrade the representation of pollutant transport, dispersion and entrainment in numerical simulations (Zhong et al 2007;Jiang et al 2008). This is partly because the PBL depth is an important turbulence length scale used in boundary-layer parametrizations.…”

Section: Introductionmentioning

confidence: 99%

Estimate of Boundary-Layer Depth Over Beijing, China, Using Doppler Lidar Data During SURF-2015

Huang

Gao

Miao

et al. 2016

Boundary-Layer Meteorol

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Planetary boundary-layer (PBL) structure was investigated using observations from a Doppler lidar and the 325-m Institute of Atmospheric Physics (IAP) meteorological tower in the centre of Beijing during the summer 2015 Study of Urban-impacts on Rainfall and Fog/haze (SURF-2015) field campaign. Using six fair-weather days of lidar and tower data under clear to cloudy skies, we evaluate the ability of the Doppler lidar to probe the urban boundary-layer structure, and then propose a composite method for estimating the diurnal cycle of the PBL depth using the Doppler lidar. For the convective boundary layer (CBL), a threshold method using vertical velocity variance (σ 2 w > 0.1 m 2 s −2 ) is used, since it provides more reliable CBL depths than a conventional maximum wind-shear method. The nocturnal boundary-layer (NBL) depth is defined as the height at which σ 2 w decreases to 10 % of its near-surface maximum minus a background variance. The PBL depths determined by combining these methods have average values ranging from ≈270 to ≈1500 m for the six days, with the greatest maximum depths associated with clear skies. Release of stored and anthropogenic heat contributes to the maintenance of turbulence until late evening, keeping the NBL near-neutral and deeper at night than would be expected over a natural surface. The NBL typically becomes more shallow with time, but grows in the presence of low-level nocturnal jets. While current results are promising, data over a broader range of conditions are needed to fully develop our PBL-depth algorithms.

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“…However, at night, the dry bias decreases to 1.40 g kg −1 and 2.36 g kg −1 for WRF and MM5, respectively. Zhong et al (2007) modeled water vapor at the UH-CC and saw biases of 1.38 during the day, −0.63 at night, and 0.37 for the overall value, which indicated overestimation of moisture during the day and underestimation at night. The difference in the two models' moisture bias could be attributed to the different land initialization schemes used for the two models, but in either case temperature performance during the entire study period appears to be affected by more than the water vapor mixing ratios.…”

Section: Water Vapormentioning

confidence: 99%

“…1). This location was selected both because it is the location of previous field studies Zhong et al, 2007) and is clear of surrounding structures that would interfere with the natural meteorological processes. Its micrometeorological setup is comprehensively described in Clements et al (2007).…”

Section: Locationmentioning

confidence: 99%

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MM5 v3.6.1 and WRF v3.5.1 model comparison of standard and surface energy variables in the development of the planetary boundary layer

Wilmot

Rappenglück

et al. 2014

Geosci. Model Dev.

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Abstract. Air quality forecasting requires atmospheric weather models to generate accurate meteorological conditions, one of which is the development of the planetary boundary layer (PBL). An important contributor to the development of the PBL is the land-air exchange captured in the energy budget as well as turbulence parameters. Standard and surface energy variables were modeled using the fifth-generation Penn State/National Center for Atmospheric Research mesoscale model (MM5), version 3.6.1, and the Weather Research and Forecasting (WRF) model, version 3.5.1, and compared to measurements for a southeastern Texas coastal region. The study period was 28 August-1 September 2006. It also included a frontal passage.The results of the study are ambiguous. Although WRF does not perform as well as MM5 in predicting PBL heights, it better simulates energy budget and most of the general variables. Both models overestimate incoming solar radiation, which implies a surplus of energy that could be redistributed in either the partitioning of the surface energy variables or in some other aspect of the meteorological modeling not examined here. The MM5 model consistently had much drier conditions than the WRF model, which could lead to more energy available to other parts of the meteorological system. On the clearest day of the study period, MM5 had increased latent heat flux, which could lead to higher evaporation rates and lower moisture in the model. However, this latent heat disparity between the two models is not visible during any other part of the study. The observed frontal passage affected the performance of most of the variables, including the radiation, flux, and turbulence variables, at times creating dramatic differences in the r 2 values.

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Impact of turbulence, land surface, and radiation parameterizations on simulated boundary layer properties in a coastal environment

Cited by 40 publications

References 24 publications

Evaluation of Planetary Boundary Layer Scheme Sensitivities for the Purpose of Parameter Estimation

Evaluation of Planetary Boundary Layer Scheme Sensitivities for the Purpose of Parameter Estimation

Estimate of Boundary-Layer Depth Over Beijing, China, Using Doppler Lidar Data During SURF-2015

MM5 v3.6.1 and WRF v3.5.1 model comparison of standard and surface energy variables in the development of the planetary boundary layer

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