In contrast to our hypothesis, both approaches were similarly effective in removing the observed phase difference between the available energy and the turbulent heat ﬂuxes and improved the fraction of variance in turbulent heat ﬂuxes explained by the avail- able energy ( Fig. 7 ). The main reason for the rejection of our hypothesis is the close correspondence between the average incli- nation and aspect of the chosen approximate footprint area (100 x the measurement height) with inclination and aspect of the main source areas ( Fig. 1 ) and the limited sensitivity of the correction (Eqs. 3–5) to small angular differences ( Figs. 4 and 8 ). This result is thus speciﬁc to the present study site, which is characterised by relatively large variability in inclination, to which the correction exhibits relatively little sensitivity ( Fig. 8 ), and a relatively more uniform aspect ( Fig. 1 ). A more general conclusion from this study thus is that a simpler approach sufﬁces as long as inclination and aspect used in the correction are reasonably representative of the source area contributing most to the measured latent and sensible heat ﬂuxes, with a greater precision required in the speciﬁcation of the average aspect. Such an approach also avoids relying heavily on detailed 2D footprint modelling, which in complexterrain is inher- ently uncertain ( Finnigan, 2004 ). In situations where the footprint is composed of pixels of more contrasting inclination and, in partic- ular, aspect ( Fig. 8 ), we can expect the footprint-weighted approach to yield better netradiation estimates.
Abstract. Surface solar radiation is an important parame- ter in surface energybalance models and in estimation of evapotranspiration. This study developed a DEM based ra- diation model to estimate instantaneous clear sky solar ra- diation for surface energybalance system to obtain accurate energy absorbed by the mountain surface. Efforts to improve spatial accuracy of satellite based surface energy budget in mountainous regions were made in this work. Based on eight scenes of Landsat TM/ETM+ (Thematic Mapper/Enhanced Thematic Mapper+) data and observations around the Qo- molangma region of the Tibetan Plateau, the topographi- cal enhanced surface energybalance system (TESEBS) was tested for deriving netradiation, ground heat flux, sensible heat flux and latent heat flux distributions over the heteroge- neous land surface. The land surface energy fluxes over the study area showed a wide range in accordance with the sur- face features and their thermodynamic states. The model was validated by observations at QOMS/CAS site in the research area with a reasonable accuracy. The mean bias of net radia- tion, sensible heat flux, ground heat flux and latent heat flux is lower than 23.6 W m −2 . The surface solar radiation esti- mated by the DEM based radiation model developed by this study has a mean bias as low as − 9.6 W m −2 . TESEBS has a decreased mean bias of about 5.9 W m −2 and 3.4 W m −2 for sensible heat and latent heat flux, respectively, compared to the Surface EnergyBalance System (SEBS).
Scientific) and an open path gas analyzer (LI 7500 by LICOR Industry) located at the top of a tower approximately 5 m above the ground. High frequency (20 Hz) measurements are stored in a compact flash of 2 Gb connected to the data logger CR5000 (Camp- bell Scientific) and downloaded in situ weekly. Only three wind velocity components: sonic temperature, vapor and carbon dioxide concentrations (raw data) are stored in the compact flash. Simultaneously, netradiation —measured by a radiometer (CNR1 by Kipp & Zonen) at a height of 4.5 m—, soil heat flux —measured with a flux plate (HFP01 by Campbell Scientific) at a depth of 6 cm from the ground and tested according to the Masseroni et al. (2013a) method— and soil temperature —measured by two thermocouples at a depth of 4 and 8 cm from the ground— are stored on the data logger in different memory tables. Soil moisture (detected by a CS 616 probe by Campbell Scientific) at different levels (10, 30 and 50 cm) and rain are also measured in the island. Averaged fluxes are calculated over a time step of 30 min.
utoledo.edu/lees/ECP/ECP.html) (Noormets et al. 2007; 2010) for sites I, II, and III, respectively, which were corrected by the double rotation method. The turbulent fluxes were adjusted for fluctuations in air density using the Webb-Pearman-Leuning expression (Webb et al. 1980). A series of data quality controls were used in the EC_Pro- cessor; for example, data quality was judged by atmos- pheric stability. Obvious outliers were removed, such as anomalous or spurious data that were caused by sensor malfunction, sensor maintenance, rainfall events, IRGA calibration, power failure, etc. A friction velocity u* (Goulden et al. 1996) of <0.15 m s −1 was used in this study (Zhang et al. 2007). Following these quality tests, the remaining data were classified as ‘good data’ to be submit- ted for analysis. Consequently, 52%, 42%, and 40% of the July–September growing season H and LE data obtained from our EC systems of sites I, II, and III, respectively, were discarded in Experiment 1. We did not intend to gap-fill the data and only the ‘good data ’ were used in this energybalanceclosure analysis.
In addition to the EC system above, for the last few decades, the large aperture scintillometer (LAS) has been widely used to measure turbulent fluxes, and reliable results have been obtained for both homogeneous and heteroge- neous underlying surfaces (Hoedjes et al., 2002; Meijninger et al., 2002a). A LAS can obtain the area-averaged sensi- ble heat flux, and the area-averaged evapotranspiration (ET) can be derived from the energybalance equation if the sur- face available energy (the netradiation minus the soil heat flux) is known (Meijninger et al., 2002b). Because the path lengths of the scintillometer are comparable to the pixel size of satellite images and area-averaged surface fluxes are ob- tained, the scintillometer has broad applications (McAneney et al., 1995; Foken et al., 2010). However, the LAS also has its limitations, such as meteorological limitations in long- term operations, which include precipitation, poor visibility, and weak turbulence, and methodological limitations such as signal saturation, inner-scale dependence of the signal, and tower vibrations (Moene et al., 2009). Thus, data process- ing must be carried out carefully, especially under complex conditions (Meijninger et al., 2002a).
cross-checking of the available energy were limited. Applied cross checks for netradiation (modelling, referenc- ing to nearby stations and ratio of netradiation to global radiation) did not reveal relevant uncertainties. Heat storage of sensible heat J H , latent heat J E , heat storage of biomass J veg and heat storage due to photosynthesis J C were of minor importance during day but of some importance during night, where J veg turned out to be the most important one. Comparisons of calculated storage terms (J E , J H ) at different towers of one site showed good agreement indicating that storage change calculated at a single point is representative for the whole canopy at sites with moderate heterogeneity. The uncertainty in AE was assessed on the basis of literature values and the results of the applied cross checks for netradiation. The absolute mean uncertainty of AE was estimated to be between 41 and 52 W m −2 (10–11 W m −2 for the sum of the storage terms J and soil heat flux G) during mid-day (approxi- mately 12% of AE). At night, the absolute mean uncertain- ty of AE varied from 20 to about 30 W m −2 (approximately 6 W m −2 for J plus G) resulting in large relative uncertainties as AE itself is small. An inspection of the energybalance showed an improvement of closure when storage terms were included and that the imbalance cannot be attributed to the uncertainties in AE alone.
In this paper, we attempted to identify and correct the root causes of lack of energyclosure in three agricul- tural fields. We found that the energy equation suffered most from imbalance during the cold non-growing sea- son. This might strongly be attributed to freeze/thaw in a snowpack, as confirmed by Hoffman et al. . For future research, we recommend that the height of snow and ice conditions also be recorded. Scatter plots of po- tential covariates vs independent variables showed that there was a systematic error of 19 W m -2 , which could be immediately eliminated. Using the technique suggested by Higgins , we conducted an a-posteriori analysis (CMLR) to quantify the contribution of each variable to the lack of energyclosure. Even though Higgins sug- gests that data analysis for a short period of one week is sufficient, Figure 4 shows that the contribution of each covariate varies throughout the year, and the process is mainly driven by prevailing hydrometeorological condi- tions. The dynamics of the sensible heat balancing coefficient during the growing season resembles LAI even though the instrument specification limits the error of netradiation to 4%. Figure 4 shows that there may exist greater overestimation in netradiation during the growing season. Even though quantification of all of the com- ponents of the energy equation was not feasible, the significance of advection terms was indirectly investigated. In line with Higgins’ findings , the impact of advection on energy imbalance is minimal. Storage in the soil was not precisely estimated and we corrected this through a-posteriori analyses. The overall trend in Figure 5 might suggest that there is a potential for correcting the latent and sensible heat fluxes according to monthly go- verning hydrometeorological conditions; however, in consideration of the trend for each field, precise quantifi- cation of latent heat flux is still site-specific.
The accurate determination of surface energybalance components in different terrestrial ecosystems is an essential prerequisite to understanding and modeling the interaction between ecosystems and ambient en- vironments, which are linked with the hydrological cycle, climate change, plant productivity, and carbon budgets (Wilson et al., 2002; Castellvi et al., 2008; Bormann, 2011). Eddy covariance (EC) has been deemed as a preferred method for measuring sur- face energy flux and balance (Mauder et al., 2007). However, the lack of energyclosure is unresolved, and a full guidance on experimental set up and raw data processing for the EC system is still unavail- able. Typically, independent measurements of fluxes accounted for 70-90% of measured netradiation, as reported by studies in the last decade (Wilson et al., 2002; Jacobs et al., 2008; Leuning et al., 2012). Generally, the failure in the energybalanceclosure was attributed to the discrepancy of the source among various flux components; inhomogeneous surface cover and soil characteristics; flux divergence arising from transport that is multi-dimensional; the missed very low and/or high-frequency fluctuations of flux- es; turbulent dispersive fluxes; measurement errors related to the sensor separation; frequency response; alignment problems, and interference from tower or instrument-mounting structures (Cleugh and Roberts, 1994; Foken and Oncley, 1995; Laubach and Teich- mann, 1999; Twine et al., 2000; Wilson et al., 2002; Masseroni et al., 2012).
In the winter environment, pavement temperature has a significant influence on highway maintenance and safety issues concerned with snow and ice management. Temperature influences the efficacy of freezing point depressant chemicals and plowing operations as well as simply ascertaining whether available water will freeze or melt. A forecasting model chain that allows prediction of pavement temperature in topographically varied terrain has been developed and is being tested on US highway I-90, which crosses Bozeman Pass, Montana. The chain is initiated with the meteorological forecast ETA model calculated on 20 km spacing. This is refined to a 1 km spacing using ARPS, a meso-scale meteorological forecasting model. These results are then interpolated to essentially provide a 30 m resolution weather forecast. Finally, RadThermRT is implemented to calculate pavement temperature at this 30 m resolution. The 30 m resolution was chosen since it coincides with digital elevation maps (DEM) available from the US Geological Survey. The DEM’s are incorporated into RadThermRT, where terrain maps used for the thermal calculations are constructed. The RadthermRT grid is in effect draped over the DEM to provide a three dimensional thermal topography whereby each 30 m element or “facet” is given thermal characteristics appropriate to the particular material type. For example, the thermal conductivity of rock, grassland, snow or pavement is appropriately assigned to a facet. Utilizing the spatially calculated meteorological inputs, the energybalance of the terrain surface is calculated for each facet and the surface temperature is forecast for each time interval. The aspect and orientation of the terrain surface takes into account the influence of radiation exchange between facets as well as the shadowing of direct solar and the sky view factor.
This present study develops a coupled remote sensing and SEBTA to estimate the actual ET under heterogeneous ter- rain, which is geared toward integrating the energybalance principle and aerodynamics turbulence theory with varying terrain and landscape effects. With the aid of DEM and LULC, the SEBTA enables us to account for the impacts of heterogeneous terrain and LULC on the ET estimation. DEM helps the calculation of netradiation and an adjustment on temperature difference. Yet the advection terms in relation to topography are hard to be included. The affects of ki- netic parameters (roughness and zero-plane displacement) in relation to LULC and terrain factors (elevation, aspect, and slope) produced by the DEM database were synergistically woven together within the simulation steps. Besides, the dry and wet pixels embedded in MODIS images can be automati- cally discerned so that the DAET can be simulated by a more accurate way. Such a strategy not only expands the applica- tion potentials but also increases the maneuverability of the SEBTA implementation at a practical level.
water-use efficiency. Baldocchi (1994) proposed utilizing the ratio of NCE:ET within an ecosystem as a suitable substitute for water use efficiency. Ratios of NCE:ET (net carbon exchange in g C per kg of water [ET]) are shown in Fig. 3.8, as a negative ratio. References to NCE:ET throughout this paper will refer to the negative ratio, where high NCE:ET displays greater water use efficiency, and a low NCE:ET likewise. By this measure water use efficiency within the shrub watershed was low both years during the growing season, which mirrors our observations of decreased photosynthesis (Fig. 3.4) and increased ET (Fig. 3.7) in contrast to the sites in an annually burned watershed (upland and lowland). Of those sites, the annually burned lowland showed a greater NCE:ET ratio in 2007, but the upland displayed higher ratios for most of the summer from Jul – Sep in 2008. This indicates that during times of environmental stress (like that experienced in 2007) lowlands have an advantage over other terrain locales due to the greater availability of water and nutrients associated with deep soils. Hilltops tend to receive higher winds as well, which dry out the soil sooner than a similar lowland, which is more likely to experience decreased winds resulting from flow distortion around landscape features/hills. As heat and water stress increase, C 4 grasses in the lowland partition their water intake, and
Figure 1 presents the evaluation of Eq. (1) for each grid cell at 50 m above ground on 16 May at 00z using mass weighted time average winds, instantaneous winds with cartesian geometric vertical velocity (w) and instantaneous winds with sigma dot ( σ ˙ ). The differences in divergence at 50 m are representative of the differences found within the PBL for other dates. The wind divergence is small and al- most identical when using time-average wind or instanta- neous winds with σ ˙ . Non-zero values come from uncertain- ties in converting the winds onto the FLEXPART vertical co- ordinate, or due to non-hydrostatic terms in the WRF model. The wind divergence is larger and more variable using the instantaneous wind with w, especially in complexterrain. However, no differences are found between wind divergences calculated by the three methods over flat terrain (either over the ocean or Central Valley). The strong divergence in com- plex terrain is the consequence of uncertainties in w related to variations in orography.
Wake detection for the entire period of operation of the scanning pulsed Doppler lidar operated by Cornell Univer- sity (mid-January and the end of June 2017) is presented herein. However, data from Tower 20 are only available from March; thus the characterization of wake centre position as a function of prevailing meteorology can only be considered for March–June, inclusive. The Galion 4000 lidar has a wave- length of 1.56 µm, a pulse length of 30 m and a range of up to 4 km (Wang et al., 2015). The instrument was operated from 980 m northeast of the wind turbine at a location in the cen- tral valley (Fig. 1). Pre-deployment planning focussed on de- velopment of an optimal scanning geometry for the scanning Doppler lidar sufficient for acquiring a data set to rigorously evaluate an objective processing methodology and to pro- vide quantitative metrics of the location and characteristics of wind turbine wakes in complexterrain. The scan configu- ration described below is thus designed to permit continuous autonomous operation in the long-term period and balance having sufficiently high-density scans to permit identifica- tion of the wake (in both the time and space domains) while not defining too small an overall arc span that would pre- clude collection of a meaningful number of cases. This mea- surement strategy was informed by the wind climatology for the site, and results from the test experiment Perdigão 2015 (Vasiljevi´c et al., 2017) indicated that the streamline defor- mation at and downwind of the ridge is highly variable and associated with a wide range of wake behaviour, including lofting and descending, and follows the terrain. In the fol- lowing Sect. 3, the creation of the scanning geometry and development of the automated processing algorithm are de- scribed.
et al., 2005; Prigent et al., 2005]. In wind tunnel studies that assessed element con ﬁ guration Cheng et al.  and Brown et al.  found that the roughness element den- sity, rather than con ﬁ guration, had the greatest in ﬂ uence on shear stress partitioning. Most aeolian transport ﬁ eld studies only consider discrete roughness elements such as vegeta- tion, but the performance of sediment entrainment schemes for surfaces with continuous microroughness is less well quanti ﬁ ed [MacKinnon et al., 2004] or parameterized using grain size [Darmenova et al., 2009]. Playas (or salt pans [Shaw and Bryant, 2011]) and small-scale rocky terrain surfaces (e.g., desert stony surfaces [Bullard et al., 2011] and sandar [Prospero et al., 2012]) typically comprise crusts or rock patterns of connected roughness elements at different scales. Although these elements are shorter than more commonly studied vegetation elements [e.g., Eamer and Walker, 2010; Brown and Hugenholtz, 2011; Weligepolage et al., 2012; Paul-Limoges et al., 2013], they still have the potential to signi ﬁ cantly alter z o and the threshold wind stress
validation against wind farms located in complexterrain. This paper aims to help fill this gap through study of wind turbines in moderately complexterrain. Efforts have been made to identify the effect of atmospheric stability on the wake data, but also as will be seen, these effects turn out to be relatively modest in this case.
Boundary-layer studies of mountainous terrain have mainly focused on global characteristics, such as thermal stratification, boundary-layer growth rates, circulation patterns and valley winds. The relatively few studies devoted to the turbulence structure over non-flat terrain have mainly been restricted to comparatively gentle hills. In , the nature of turbulent kinetic energy in a steep and narrow Alpine valley in Switzerland under fair- weather summertime conditions was investigated for a detailed case study, in which the evaluation of aircraft data was combined with the application of high-resolution large-eddy simulations using the numerical model ARPS. Excellent correlation was established between surface heat flux and the up-valley wind speed. The measure-
Location representativeness of RCM-simulated climate can in principle be measured by the temporal correlation between simulated and observed climate in a perfect boundary setting. However, internal climate variability hampers the estimation. An RCM, even if driven with perfect boundary conditions, is not designed to correctly simulate the observed day-to-day variability at the grid-box scale (Weisse and Feser, 2003; Wong et al., 2014); away from the boundary conditions, complex weather dynamics will always result in consider- able random deviations of simulated from observed weather system trajectories. Although such mesoscale internal atmo- spheric variability reduces the correlation between simula- tion and observations, it does not reduce the location repre- sentativeness. Yet, mesoscale internal atmospheric variability generally occurs at short timescales and will be averaged out at longer timescales.