Comments and further analysis on effective roughness lengths for use in numerical three-dimensional models

Taylor, Peter A.

doi:10.1007/bf00125144

Cited by 116 publications

(65 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There has been abundant literature on the subject from back in the 1990s, mostly based on theoretical works deriving deterministic [41] or statistical [42] relationships between local and regional parameters for land-atmosphere exchange modelling. For roughness length, Wassenaar et al [43] conclude that a geometric averaging of the roughness length is performing best; this is also the scaling proposed by Taylor [44].…”

Section: Introductionmentioning

confidence: 64%

Evaluation and Aggregation Properties of Thermal Infra-Red-Based Evapotranspiration Algorithms from 100 m to the km Scale over a Semi-Arid Irrigated Agricultural Area

et al. 2017

View full text Add to dashboard Cite

Evapotranspiration (ET) estimates are particularly needed for monitoring the available water of arid lands. Remote sensing data offer the ideal spatial and temporal coverage needed by irrigation water management institutions to deal with increasing pressure on available water. Low spatial resolution (LR) products present strong advantages. They cover larger zones and are acquired more frequently than high spatial resolution (HR) products. Current sensors such as Moderate-Resolution Imaging Spectroradiometer (MODIS) offer a long record history. However, validation of ET products at LR remains a difficult task. In this context, the objective of this study is to evaluate scaling properties of ET fluxes obtained at high and low resolution by two commonly used Energy Balance models, the Surface Energy Balance System (SEBS) and the Two-Source Energy Balance model (TSEB). Both are forced by local meteorological observations and remote sensing data in Visible, Near Infra-Red and Thermal Infra-Red spectral domains. Remotely sensed data stem from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and MODIS sensors, respectively, resampled at 100 m and 1000 m resolutions. The study zone is a square area of 4 by 4 km 2 located in a semi-arid irrigated agricultural zone in the northwest of Mexico. Wheat is the dominant crop, followed by maize and vegetables. The HR ASTER dataset includes seven dates between the 30 December 2007 and 13 May 2008 and the LR MODIS products were retrieved for the same overpasses. ET retrievals from HR ASTER products provided reference ET maps at LR once linearly aggregated at the km scale. The quality of this retrieval was assessed using eddy covariance data at seven locations within the 4 by 4 km 2 square. To investigate the impact of input aggregation, we first compared to the reference dataset all fluxes obtained by running TSEB and SEBS models using ASTER reflectances and radiances previously aggregated at the km scale. Second, we compared to the same reference dataset all fluxes obtained with SEBS and TSEB models using MODIS data. LR fluxes obtained by both models driven by aggregated ASTER input data compared well with the reference simulations and illustrated the relatively good accuracy achieved using aggregated inputs (relative bias of about 3.5% for SEBS and decreased to less than 1% for TSEB). Results also showed that MODIS ET estimates compared well with the reference simulation (relative bias was down to about 2% for Remote Sens. 2017, 9, 1178; doi:10.3390/rs9111178www.mdpi.com/journal/remotesensing Remote Sens. 2017, 9, 1178 2 of 27 SEBS and 3% for TSEB). Discrepancies were mainly related to fraction cover mapping for TSEB and to surface roughness length mapping for SEBS. This was consistent with the sensitivity analysis of those parameters previously published. To improve accuracy from LR estimates obtained using the 1 km surface temperature product provided by MODIS, we tested three statistical and one deterministic aggregation rules for the most sens...

show abstract

Section: Introductionmentioning

confidence: 64%

Evaluation and Aggregation Properties of Thermal Infra-Red-Based Evapotranspiration Algorithms from 100 m to the km Scale over a Semi-Arid Irrigated Agricultural Area

et al. 2017

View full text Add to dashboard Cite

show abstract

“…Station data were used for bias correction of the modelled wind. The 1-km 2 resolution was reached by transforming the wind speed to the local roughness length using the logarithmic wind profile law (Taylor 1987).…”

Section: Wind Componentsmentioning

confidence: 99%

High-resolution grids of hourly meteorological variables for Germany

Krähenmann

Brienen

Imbery

et al. 2016

Theor Appl Climatol

View full text Add to dashboard Cite

We present a 1-km 2 gridded German dataset of hourly surface climate variables covering the period 1995 to 2012. The dataset comprises 12 variables including temperature, dew point, cloud cover, wind speed and direction, global and direct shortwave radiation, down-and up-welling longwave radiation, sea level pressure, relative humidity and vapour pressure. This dataset was constructed statistically from station data, satellite observations and model data. It is outstanding in terms of spatial and temporal resolution and in the number of climate variables. For each variable, we employed the most suitable gridding method and combined the best of several information sources, including station records, satellite-derived data and data from a regional climate model. A module to estimate urban heat island intensity was integrated for air and dew point temperature. Owing to the low density of available synop stations, the gridded dataset does not capture all variations that may occur at a resolution of 1 km 2 . This applies to areas of complex terrain (all the variables), and in particular to wind speed and the radiation parameters. To achieve maximum precision, we used all observational information when it was available. This, however, leads to inhomogeneities in station network density and affects the long-term consistency of the dataset. A first climate analysis for Germany was conducted.

show abstract

“…The result for surface roughness, however, is quite different (Taylor, 1987). This method yields a grid-averaged roughness length scale which corresponds to an algebraic average of the friction velocity over the grid, and has been in fairly common use for several decades (Kung, 1963;Vihma and Savijarvi, 1991 Richardson number represents the ratio between buoyant and shear production of turbulent kinetic energy and is given by the relationship:…”

Section: Surface Moisture Availabilitymentioning

confidence: 99%

Role of surface characteristics in urban meteorology and air quality

Sailor

1993

View full text Add to dashboard Cite

Comments and further analysis on effective roughness lengths for use in numerical three-dimensional models

Cited by 116 publications

References 9 publications

Evaluation and Aggregation Properties of Thermal Infra-Red-Based Evapotranspiration Algorithms from 100 m to the km Scale over a Semi-Arid Irrigated Agricultural Area

Evaluation and Aggregation Properties of Thermal Infra-Red-Based Evapotranspiration Algorithms from 100 m to the km Scale over a Semi-Arid Irrigated Agricultural Area

High-resolution grids of hourly meteorological variables for Germany

Role of surface characteristics in urban meteorology and air quality

Contact Info

Product

Resources

About