Evaluation of Monin–Obukhov and Bulk Richardson Parameterizations for Surface–Atmosphere Exchange

Lee, Temple R.; Buban, Michael

doi:10.1175/jamc-d-19-0057.1

Cited by 14 publications

(12 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The setup is presented in Figure 1 and the operating parameters of all lidars are listed in Table 1. The land cover at the EB stations was a mixture of grassland and soybeans at TWR 1, native grassland at TWR 2, mature soybeans at TWR 3, and pasture at TWR 4 (Lee & Buban, 2020; Wulfmeyer at al., 2018).…”

Section: The Land Atmosphere Feedback Experiments (Lafe)mentioning

confidence: 99%

“…Gradient and further flux measurements are made with additional sensors located at approx. 10 m above the canopy (Lee & Buban, 2020; Lee et al., 2019). Further insight in SL profiles and gradients have been achieved with sensors at different levels at high towers such as at the German Weather Service Lindenberg Meteorological Observatory ‐ Richard Assmann Observatory (Neisser et al., 2002), the Boulder tower (Wolfe & Lataitis, 2018), the WLEF‐TV tower in Wisconsin (Berger et al., 2001), the tower in Cabauw (Röckmann et al., 2016), and the Amazon Tall Tower Observatory (Andreae et al., 2015).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Simultaneous Observations of Surface Layer Profiles of Humidity, Temperature, and Wind Using Scanning Lidar Instruments

et al. 2022

View full text Add to dashboard Cite

The development of the planetary boundary layer (PBL) is related to the exchange of momentum, energy, and water between the atmosphere and the land surface as well as to the resulting feedback processes in the land-atmosphere (L-A) system (Santanello et al., 2018). The representation and the parametrization of surface fluxes in models is crucial in weather and climate models for reliable forecasts and simulations. The surface layer (SL) is the direct connection between the land-surface and the atmosphere. The behavior of SL profiles depends on the vertical stability in the atmosphere as well as the soil and the land cover properties and their heterogeneities.In order to describe the dependence of SL profiles on the surface fluxes, flux-gradient relationships have been developed. These relationships are fundamental for the parameterization of fluxes in weather forecast, climate and earth system models. The most prominent and widely used scheme is the Monin-Obukhov similarity theory (MOST; e.g., Monin & Obukhov, 1954;Obukhov, 1971). It relates the vertical gradients of wind, potential temperature and specific humidity in the SL to fluxes of momentum, heat and moisture in combination with dimensionless similarity functions. These similarity functions depend on the atmospheric stability and are typically classified by the bulk Richardson number R b . The height z above the canopy is scaled with the Monin-Obukhov length L. MOST is used for the parameterization of surface turbulent fluxes in almost all weather forecast and climate models such as in the SL scheme of the Weather Research and Forecast (WRF) model (Jiménez et al., 2012). However, MOST is not the only option for the description of flux-gradient relationships in the SL. Another approach relates the fluxes and the gradients in a similar way as in MOST but uses a similarity function, which is dependent on R b (Lee & Buban, 2020). With increasing numbers and different kinds of observations, machine

show abstract

Section: The Land Atmosphere Feedback Experiments (Lafe)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Simultaneous Observations of Surface Layer Profiles of Humidity, Temperature, and Wind Using Scanning Lidar Instruments

et al. 2022

View full text Add to dashboard Cite

show abstract

“…The absence of explicit documentation of this effect in the literature might be related to the fact that wet soils with short vegetation and large solar irradiation are not so common [being the aforementioned work of Lee and Buban (2020) an exception]. The pioneering works of Businger or Dyer were made essentially over dry terrain.…”

Section: Daytime Cases With Moist Soilmentioning

confidence: 99%

Flux–Gradient Relationships Below 2 m Over a Flat Site in Complex Terrain

Martí

Martínez‐Villagrasa

Cuxart

2022

Boundary-Layer Meteorol

View full text Add to dashboard Cite

The surface–atmosphere turbulent exchange fluxes are experimentally determined using the eddy-covariance method. Their estimation using profiles of the variables of interest is a less costly alternative, although restricted to certain ranges of stability and assumed to hold for relatively flat and homogeneous terrain. It relays usually on the prescription of the roughness lengths for momentum, heat and matter, the latter two being adjustable parameters with unclear physical significance. The relations are derived with data from screen level to a few tens of metres upward. The application of these expressions using data only at one level in the surface layer implies assuming zero wind speed and the land surface temperature at their respective roughness lengths. The latter is a quantity that experimentally can only be determined radiatively with a substantial uncertainty. In this work the flux-profile relationships for momentum and sensible heat are assessed over a flat site in moderately inhomogeneous complex terrain in the southern pre-Pyrenees, using data between 2 m and the surface. The main findings are that (i) the classical expressions hold in the daytime for most of the dataset, (ii) the iterative estimations using the Obukhov length and the direct ones using the bulk Richardson number provide very similar results, (iii) using a second observation of temperature avoids a radiometric measure of land surface temperature and the prescription of a thermal roughness length value, (iv) the estimations over wet terrain with high irradiance depart largely from observations.

show abstract

“…Major uncertainties of the MOST method are associated with the influence of complex/heterogeneous terrain, uncertainties in prescribing vegetation roughness and corrections for atmospheric stability (Holwerda et al, 2012;Sun et al, 2020;van Dijk et al, 2015;Zhou et al, 2012). Lee and Buban (2020) found that the Richardson number stability correction functions based on bulk meteorological variables yielded better agreement with field observations than using MOST relationships. These challenges are further exacerbated by the ambiguity in estimating the difference between r aM and the r a for heat transfer (r aH ), whereby complexity is added due to the inequality of LST and the aerodynamic temperature (T 0 ) (Paul et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

The role of aerodynamic resistance in thermal remote sensing-based evapotranspiration models

Trebs¹,

Mallick²,

Bhattarai

et al. 2021

Preprint

View full text Add to dashboard Cite

&#8216;Aerodynamic resistance&#8217; (hereafter ra) is a preeminent variable in the modelling of evapotranspiration (ET), and its accurate quantification plays a critical role in determining the performance and consistency of thermal remote sensing-based surface energy balance (SEB) models for estimating ET at local to regional scales. Atmospheric stability links ra with land surface temperature (LST) and the representation of their interactions in the SEB models determines the accuracy of ET estimates.The present study investigates the influence of ra and its relation to LST uncertainties on the performance of three structurally different SEB models by combining nine OzFlux eddy covariance datasets from 2011 to 2019 from sites of different aridity in Australia with MODIS Terra and Aqua LST and leaf area index (LAI) products. Simulations of the latent heat flux (LE, energy equivalent of ET in W/m2) from the SPARSE (Soil Plant Atmosphere and Remote Sensing Evapotranspiration), SEBS (Surface Energy Balance System) and STIC (Surface Temperature Initiated Closure) models forced with MODIS LST, LAI, and in-situ meteorological datasets were evaluated using observed flux data across water-limited (semi-arid and arid) and radiation-limited (mesic) ecosystems.Our results revealed that the three models tend to overestimate instantaneous LE in the water-limited shrubland, woodland and grassland ecosystems by up to 60% on average, which was caused by an underestimation of the sensible heat flux (H). LE overestimation was associated with discrepancies in ra retrievals under conditions of high atmospheric instability, during which errors in LST (expressed as the difference between MODIS LST and in-situ LST) apparently played a minor role. On the other hand, a positive bias in LST coincides with low ra and causes slight underestimation of LE at the water-limited sites. The impact of ra on the LE residual error was found to be of the same magnitude as the influence of errors in LST in the semi-arid ecosystems as indicated by variable importance in projection (VIP) coefficients from partial least squares regression above unity. In contrast, our results for mesic forest ecosystems indicated minor dependency on ra for modelling LE (VIP<0.4), which was due to a higher roughness length and lower LST resulting in dominance of mechanically generated turbulence, thereby diminishing the importance of atmospheric stability in the determination of ra.

show abstract

Evaluation of Monin–Obukhov and Bulk Richardson Parameterizations for Surface–Atmosphere Exchange

Cited by 14 publications

References 30 publications

Simultaneous Observations of Surface Layer Profiles of Humidity, Temperature, and Wind Using Scanning Lidar Instruments

Simultaneous Observations of Surface Layer Profiles of Humidity, Temperature, and Wind Using Scanning Lidar Instruments

Flux–Gradient Relationships Below 2 m Over a Flat Site in Complex Terrain

The role of aerodynamic resistance in thermal remote sensing-based evapotranspiration models

Contact Info

Product

Resources

About