International Satellite Land Surface Climatology Project Research Articles

Combined Use of Vegetation Density, Friction Velocity, and Solar Elevation to Parameterize the Scalar Roughness for Sensible Heat

Abstract Monin-Obukhov similarity was used to calculate sensible heat fluxes (Hc) at an array of up to 20 surface flux measurement sites on five days in 1987 and 1989 during the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment by means of spatially distributed radiometric surface temperatures from an airborne platform and ground-based data. To use Monin-Obukhov similarity, a parameterization for the scalar roughness, as a function of spatially varying leaf area index (LAI) and friction velocity (u∗), was developed from a previous, simpler parameterization. LAI was found to be significant, but the range of u∗ was too small to ascertain its significance. The parameterization was found to produce sensible heat flux values that had correlations around 0.8 with the spatially distributed sensible heat flux measurements on four of the days, but on a day with high, uniform soil moisture content, the correlation was only 0.226. It is argued that the high soil moisture values...

Sensible Heat Flux Estimation over the FIFE Site by Neural Networks

Abstract Observations from the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE) showed that it is difficult to estimate the sensible heat flux from routinely observed environmental parameters. This study, therefore, explores the use of backpropagation neural networks to elucidate the link between sensible heat flux on the one hand and horizontal wind speed, air temperature, radiometric surface temperature, net radiation, and time on the other. Data collected over the FIFE site in 1987 and 1989 were used for network training and validation. Networks trained on part of the data from a narrow range of space–time coordinates performed well over the other part, with error (rms divided by mean of observations) values as low as 0.24. This indicates the potential in neural networks for linking sensible heat flux to routinely measured meteorological variables and variables amenable to remote sensing. When the networks were tested with data from other space–times, perf...

Satellite-Sensed Distribution and Spatial Patterns of Vegetation Parameters over a Tallgrass Prairie

Abstract Remotely sensed images of vegetation density expressed as the Normalized Difference Vegetation index (NDVI) recorded during the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment were mapped on the same coordinate system covering the 20 km × 20 km experimental site. The temporal behavior of frequency distributions and semivariograms of the NDVI exhibited similarity; these distributions were quite symmetric, except near the extremes. Although values at individual locations showed considerable scatter, when averaged over the experimental area, the NDVI values were well correlated with ground-based measurements of the leaf area index. The persistence tendencies of the spatial patterns of NDVI were evaluated through correlation analysis of the images on successive days. The spatial patterns were preserved well during wet periods; they gradually changed by deep drying of the soil but were restored after heavy rainfall.

Biotic Interactivity between Grazers and Plants: Relationships Contributing to Atmospheric Boundary Layer Dynamics

Abstract During 1987 and 1988 First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE) studies conducted in the tallgrass prairie of central Kansas, variations in ungulate grazing intensity produced a patchy spatial and temporal distribution of remaining vegetation. Equally variable plant regrowth patterns contributed further to a broad array of total primary production that resulted in a pronounced mosaic of grazing impacts. This regrowth potential, derived from a relative growth rate (RGR) equation comparing ungrazed and grazed plants, determines much of the ecosystem dynamics within and among the grazed pastures and between years. Rates of change in new plant growth (ΔRGRg) ranged from −100% to +40%; however, 78% of the time in 1987 and 71% in 1988, productivity increased as a function of grazing intensity. Since plant growth potential in ungrazed (RGRug) and grazed systems (RGRg) have inherently different attributes, interactions with the abiotic environment may ...

FIFE Surface Climate and Site-Average Dataset 1987–89

This paper analyzes the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment site-average datasets for near-surface meteorology, soil moisture, and temperature; the surface fluxes of radiation, sensible, and latent heat; and the ground heat flux, for the period May 1987‐November 1989. The diurnal and seasonal variation of surface albedo for this grassland site are discussed. The coupling of precipitation, soil moisture, evaporation, pressure height to the lifting condensation level, and equivalent potential temperature (uE) on seasonal and diurnal timescales is also discussed. The 1988 data confirm the authors’ result, shown earlier from the 1987 data that over moist soils increased evapotranspiration lowers afternoon lifting condensation level and increases afternoon uE, suggesting a mechanism for a local positive feedback between soil moisture and precipitation on horizontal scales greater than 200 km. The seasonal cycle of ground heat flux and soil temperature is examined and the authors show that the coupling in the warm months between uE and soil temperature on seasonal scales is similar over land to the coupling found over warm oceans despite very different controls on the surface fluxes. The boundary layer equilibrium over the ocean is contrasted with the diurnal cycle over land, which is soil moisture dependent.

Linking Boundary Layer Circulations and Surface Processes during FIFE 89. Part II: Maintenance of Secondary Circulation

Abstract Land–atmosphere interactions are examined for three different synoptic situations during a 21-day period in the course of the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment 1989 to better understand the relationship between biophysical feedback processes, boundary layer structure, and circulations in the boundary layer. The objective is to understand how the secondary circulation discussed in Part I of this paper was able to sustain itself throughout the duration of the 1989 intensive field campaign. The study is based on diagnostic analysis of measurements obtained from a network of surface meteorology and energy budget stations, augmented with high vertical resolution radiosonde measurements. Shallow convection associated with an undisturbed boundary layer situation and rainfall occurring during two different disturbed boundary layer situations—one associated with a surface trough, the other with the passage of a cold front—led to markedly different imp...

Inverting optical reflectance to estimate surface properties of vegetation canopies

An inversion method using a simple bidirectional reflectance model and data on optical reflectances remotely-sensed from satellites has been improved to derive surface properties such as the leaf area index (LAI). Such properties are important in deriving the resistance of the vegetative canopy to uptake of gaseous trace chemicals from the atmosphere and in the study of radiation transfer processes. We found that a multi-pass retrieval technique can greatly improve a model's ability to retrieve surface properties. Because the sensitivity of the model inversion to initial values is an important issue that depends on (1) the partial derivative of reflectance with respect to each parameters to be retrieved ( R / x ) and (2) the degree of independence among model parameters, we investigated the issue with synthetic data constructed by a bidirectional reflectance model. The results revealed that, although the surface optical properties are mostly independent of each other, their initial values did have some effect on the retrieved value of the LAI, with the worse case caused by leaf angle distribution index, n, at close-to-nadir solar and view zenith angles of the reflectance data. At nearnadir angles, n and LAI were strongly correlated, and their retrieval was not unique. When applied to satellite remote sensing data obtained with the advanced very-high-resolution radiometer (AVHRR), the model-retrieved seasonal variation of surface properties agreed reasonably well with independent ground measurements made in the First International Satellite Land-Surface Climatology Project (ISLSCP) Field Experiment (FIFE) campaign. Application to Landsat data to retrieve spatial variation was less successful, largely because of the close-to-nadir solar and view zenith angles in the data.

A simple single layer model to estimate transpiration from vegetation using multi-spectral and meteorological data

A methodology is developed here to model evapotranspiration (λEc ) from the canopy layer over large areas by combining satellite and ground measurements of biophysical and meteorological variables. The model developed here follows the energy balance approach, where λEc is estimated as a residual when the net radiation (Rn), sensible heat flux (H) and ground flux (G) are known. Multi-spectral measurements from the NOAA Advanced Very High Resolution Radiometer (AVHRR) were used along with routine meteorological measurements made on the ground to estimate components of the energy balance. The upwelling long wave radiation, and H from the canopy layer were modelled using the canopy temperature, obtained from a linear relation between the Normalized Difference Vegetation Index (NDVI) and surface temperature. This method separates flux measurements from the canopy and bare soil without the need for a complex two layer model. From theoretical analysis of canopy reflectance, leaf area, and canopy resistance, a model is developed to scale the transpiration estimates from the full canopy to give an area averaged estimate from the mean NDVI of the study area. The model was tested using data collected from the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), and the results show that the modelled values of total surface evapotranspiration from the soil and canopy layers vary from the ground measurements by less than 9 per cent.

A global surface reflectivity data set for the 2.2-2.35 mu m region

The lack of surface reflectivity data in the near-infrared region and the need of this information for an on-going project on remote sounding of atmospheric pollution motivated a search for a scientific, yet practical approach to creating a global data set of surface reflectivity with seasonality at 2.2-2.35 mu m region. Since the surface reflectivity varies significantly with the type of unvegetated ground and the extent of surface vegetation coverage, attempts were first made to determine the surface reflectivity of each of the major 'components' of the Earth's surface in the spectrum region of interest. The Landsat TM band 7 data were used to derive the reflectivity values for those components. Furthermore, the global Leaf Area Index (LAI) data set from the International Satellite Land Surface Climatology Project (ISLSCP) was used to calculate the seasonal variation of the fraction of vegetation coverage of any given surface areas. A global map of reflectivity in the 2.3 mu m region is then derived by taking a weighted average of the reflectivity values of several basic components of the underlying surface. The weight of each characteristic surface component comes from its fractional area. A brief description is presented on how to calculate the fraction of vegetation coverage characterized by the green Leaf Area Fraction (LAF) from widely available Normalized Difference Vegetation Index (NDVI) data sets. Also presented is the comparison of the derived surface reflectivity by this approach with independently calculated reflectivity values from the Landsat data for some selected areas. The overall methodology can be extended to achieve a higher-resolution mapping when the required data sets become available.

Comparison of the Land-Surface Interaction in the ECMWF Reanalysis Model with the 1987 FIFE Data

Data from the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment for the summer season of 1987 are used to assess the land-surface interaction of the ECMWF reanalysis. In comparison with an earlier study, using the 1992 ECMWF operational model, the land-surface interaction is greatly improved. The bias in the incoming solar radiation has been removed, although there seems to be a small low bias in the incoming longwave, which is significant at night. The four-layer soil moisture model depicts the seasonal cycle well, and the root zone is recharged satisfactorily after major rain events. Consequently, the evaporative fraction (EF) over the season is now generally quite good. There is, however, a low bias in EF in June and high bias in October, which is probably due to the absence of a seasonal cycle in the model vegetation. The evaporative fraction also appears too high in the model just after rainfall. It also appears that the model lacks a realistic seasonal control on the soil heat flux. The surface diurnal thermodynamic cycle has two noticeable errors. The temperature minimum at sunrise is too low, because the surface uncouples too much at night under the stable boundary layer, and the incoming longwave radiation is biased low. There is also an unrealistic diurnal cycle of mixing ratio, q, with too strong a midmorning peak, and too large a fall during the day to a late afternoon minimum that is biased low. These errors in the diurnal cycle of q may feed back on the diurnal cycle of precipitation. The morning peak is partly related to the too-strong inversion at sunrise, which slows the deepening of the boundary layer. The late afternoon minimum of mixing ratio (below that of the model analysis) leads to a positive nudging of soil moisture in the analysis cycle. The model summer mixing ratio has a small high bias of 0.5 g kg21.

NOAA AVHRR land surface albedo algorithm development

The primary objective of this research is to develop a surface albedo model for the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR). The primary test site is the Konza prairie, Kansas (U.S.A.), used by the International Satellite Land Surface Climatology Project (ISLSCP) in the First ISLSCP Field Experiment (FIFE). In this research, high spectral resolution field spectrometer data was analyzed to simulate AVHRR wavebands and to derive surface albedos. Development of a surface albedo algorithm was completed by analysing a combination of satellite, field spectrometer, and ancillary data. Estimated albedos from the field spectrometer data were compared to reference albedos derived using pyranometer data. Variations from surface anisotropy of reflected solar radiation were found to be the most significant albedo-related error. Additional error or sensitivity came from estimation of a shortwave mid-IR reflectance (1.3-4.0 mu m) using the AVHRR red and near-IR bands. Errors caused by the use of AVHRR spectral reflectance to estimate both a total visible (0.4-0.7 mu m) and near-IR (0.7-1.3 mu m) reflectance were small. The solar spectral integration, using the derived ultraviolet, visible, near-IR and SW mid-IR reflectivities, was not sensitive to many clear-sky changes in atmospheric properties and illumination conditions.

Estimating spectral albedo and nadir reflectance through inversion of simple BRDF models with AVHRR/MODIS‐like data

In recent years, many computationally efficient bidirectional reflectance models have been developed to account for angular effects in land remote sensing data, particularly those from the NOAA advanced very high resolution radiometer (AVHRR), polarization and directionality of the Earth's reflectances (POLDER), and the planned EOS moderate‐resolution imaging spectrometer (MODIS) and multi‐angle imaging spectroradiometer (MISR) sensors. In this study, we assessed the relative ability of 10 such models to predict commonly used remote sensing products (nadir reflectance and albedo). Specifically, we inverted each model with ground‐based data from the portable apparatus for rapid acquisition of bidirectional observations of the land and atmosphere (PARABOLA) arranged in subsets representative of satellite sampling geometries. We used data from nine land cover types, ranging from soil to grassland (First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE)) to forest (Boreal Ecosystem‐Atmosphere Study (BOREAS)). Retrieved parameters were used in forward model runs to estimate nadir reflectance and spectral albedo over a wide range of solar angles. We rank the models by the accuracy of the estimated products and find results to be strongly dependent on the view azimuth angle range of the inversion data, and less dependent on the spectral band and land cover type. Overall, the nonlinear model of Rahman et al. [993] and the linear kernel‐driven RossThickLiSparse model [Wanner et al., 1995] were most accurate. The latter was at least 25 times faster to invert than the former. Interestingly, we found these two models were not able to match the various bidirectional reflectance distribution function (BRDF) shapes as well as other models, suggesting their superior performance lies in their ability to be more reliably inverted with sparse data sets. These results should be useful to those interested in the computationally fast normalization of bidirectional reflectance data and the estimation of radiation flux parameters (albedo, absorbed radiation) over diverse land covers.

Performance of Different Soil Model Configurations in Simulating Ground Surface Temperature and Surface Fluxes

This study compares three modifications to the one-dimensional planetary boundary layer scheme that is implemented in the σ–θ hybrid-b version of the Mesoscale Analysis and Prediction System (MAPS) and the Rapid Update Cycle (RUC). All three modifications are based on the incorporation of a simple soil model into the basic version to more accurately calculate the moisture and heat fluxes across the ground surface. The presented schemes are of increasing sophistication: the first model combines the soil model with heat and moisture budget equations for the ground surface and uses an explicit numerical scheme to compute the surface fluxes; the second model uses a more energy-conservative implicit solution for the latent and sensible surface fluxes and heat and moisture soil fluxes; the third model further incorporates a simple parameterization of the evapotranspiration process. The comparison includes the effect of different schemes on diurnal changes of surface temperature and soil heat flux. The schemes are tested for two case studies; a dry case from the O’Neill, Nebraska, Great Plains Turbulence Field Program and a moist case from the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment. Tests are performed to evaluate sensitivity to soil parameters related to thermal diffusivity and to vertical resolution of the soil scheme. Overall, the comparison supports the idea that implementation of a multilevel soil model is competitive with and can even improve the ground surface temperature forecast over that produced by the present MAPS implementation of the force restore method. The case study demonstrates that incorporation of a primitive evapotranspiration model can give positive results.

A dynamic water vapor correction method for the retrieval of land surface temperatures from the advanced very high resolution radiometer

We present a method which permits retrievals of land surface temperatures (LSTs) from AVHRR (advanced very high resolution radiometer) radiances sensed through atmospheres which may contain a large and strongly varying water vapor content. This new method is an extension of the dynamic water vapor (DWV) algorithm which was designed to retrieve sea surface temperatures. The generalization to LST retrievals recognizes that in general, land emissivities are unknown, may be spectrally dependent, and are less than unity. Because the LST retrieval problem is inherently underconstrained (there are more unknowns than radiative transfer equations), some knowledge of surface emissivity is required in order to establish upper and lower bounds on surface temperature. We demonstrate our method by comparing DWV‐LST retrievals with point surface measurements made by a cluster of eight infrared thermometers (IRTs) deployed over a grasslands prairie site in eastern Kansas in July and August 1989; this deployment was part of the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE). We find that several of the AVHRR images supplied on FIFE CD‐ROM contain navigation errors of ∼30 km, consistent with a misidentification of the Tuttle Reservoir ground control point. After correcting the navigation, we identified the IRT pixels and computed the bias and rms errors for a DWV‐IRT comparison. For night passes we obtained agreement to.+0.39±1.11 K, while for day passes the comparison yielded +4.09±3.10 K. The large daytime bias is probably the result of the IRT readings not being representative of the ∼1 km2‐scale areas sensed by AVHRR (the IRT views vegetation; the AVHRR field of view includes warmer, less well vegetated surfaces). Our results show that while a fixed‐coefficient, global split‐window algorithm does not perform well in the relatively moist FIFE atmosphere, it is quite feasible to use the DWV‐LST to derive a local split‐window algorithm whose coefficient is tuned on a per‐pass basis.

A two‐source approach for estimating turbulent fluxes using multiple angle thermal infrared observations

A recently developed two‐source model for computing the surface energy balance with directional radiometric surface temperature observations can be simplified with the use of radiometric surface temperature observations at two substantially different view angles. Such observations have been available from the Along Track Scanning Radiometer (ATSR) aboard the First European Remote Sensing Satellite (ERS‐1) and therefore could be used operationally with this simplified model. Compared to the original model formulation, the new version, 2ANGLE, does not require an estimate of the fraction of “green” or active vegetation, fg, and use of the Priestley‐Taylor parameterization for partitioning of net radiation absorbed by the canopy into latent, LE, and sensible, H, heat in order to obtain a solution. However, if one uses the Priestley‐Taylor parameterization with two radiometric observations at different view angles, then the model, 2ANGLE_PT, does not require a measurement of air temperature. The model‐derived fluxes using multiple angle radiometric surface temperature observations collected during the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), which was conducted in the tall grass prairie in eastern Kansas during the summers of 1987 and 1989, are compared to measured surface fluxes. Differences between predicted and measured H using the 2ANGLE and 2ANGLE_PT models were generally significant (i.e., >50%), while the original version, 1ANGLE_PT, yielded differences of 45–50%, on average. The 2ANGLE and 2ANGLE_PT model predictions of LE yielded differences of 25–40% with measured values, while the 1ANGLE_PT model produced differences of 15–20%, on average. Using a simple technique to estimate daytime total LE from the “instantaneous” values with the three versions of the model resulted in differences generally between 20 and 25%. A review of studies analyzing FIFE flux measurement techniques indicates that differences in half‐hourly to hourly observations of H and LE can reach 50% or greater, but typically are between 20 and 30%. Therefore the performance of the models in predicting H ranged from marginal to poor, but was generally satisfactory in estimating LE because in many cases LE was significantly larger than H. The performance of the 2ANGLE_PT model in predicting Hand LE was significantly better than the 2ANGLE model, but not as good as the original 1ANGLE_PT model. A sensitivity analysis with the three models indicated that not only were the 2ANGLE_PT model predictions unaffected by a 3 K uncertainty in the estimation of air temperature using satellite data, but also showed little sensitivity to a 1.5 K uncertainty associated with deriving an atmospherically corrected surface temperature from ATSR observations. Therefore the 2ANGLE_PT model has potential for computing regional‐scale LE operationally with a satellite‐based sensor such as the ATSR.

The Surface Heat Flux as a Function of Ground Cover for Climate Models

Abstract Surface heat fluxes were examined as a function of surface properties and meteorological conditions in a 100 km × 100 km grid square at 1-km spatial resolution centered at the location of the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE), the Forest Ecosystem Dynamics site in central Maine, and a semiarid rangeland site around Walnut Gulch, Arizona. This investigation treats the surface heat flux variability within a GCM grid box to provide insight into methods for treating that variability in climate models. The heat fluxes were calculated using NOAA AVHRR and available meteorological data. The average heat fluxes that were estimated using the various area ground-cover representations were compared with the ensemble average heat fluxes for the entire area, which were assumed to be the best representation of the heat fluxes for the areas. Average heat fluxes were estimated for the entire 100 km × 100 km area based on a single ground-cover represen...

Simulation of Atmospheric Boundary Layer Processes Using Local- and Nonlocal-Closure Schemes

A soil‐vegetation‐atmospheric boundary layer model was developed to study the performance of two localclosure and two nonlocal-closure boundary layer mixing schemes for use in meteorological and air quality simulation models. Full interaction between the surface and atmosphere is achieved by representing surface characteristics and associated processes using a prognostic soil‐vegetation scheme and atmospheric boundary layer schemes. There are 30 layers in the lowest 3 km of the model with a high resolution near the surface. The four boundary layer schemes are tested by simulating atmospheric boundary layer structures over densely and sparsely vegetated regions using the observational data from the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE) and from Wangara. Simulation results indicate that the near-surface turbulent fluxes predicted by the four boundary layer schemes differ from each other, even though the formulation used to represent the surface-layer processes is the same. These differences arise from the differing ways of representing subgrid-scale vertical mixing processes. Results also indicate that the vertical profiles of predicted parameters (i.e., temperature, mixing ratio, and horizontal winds) from the four mixed-layer schemes differ from each other, particularly during the daytime growth of the mixed layer. During the evening hours, after the mixed layer has reached its maximum depth, the differences among these respective predicted variables are found to be insignificant. There were some general features that were associated with each of the schemes in all of the simulations. Compared with observations, in all of the cases the simulated maximum depths of the boundary layer for each scheme were consistently either lower or higher, superadiabatic lapse rates were consistently either stronger or weaker, and the intensity of the vertical mixing was either stronger or weaker. Also, throughout the simulation period in all case studies, most of the differences in the predicted parameters are present in the surface layer and near the top of the mixed layer.

A soil‐canopy‐atmosphere model for use in satellite microwave remote sensing

Regional and global scale studies of land‐surface‐atmosphere interactions require the use of observations for calibration and validation. In situ field observations are not representative of the distributed nature of land surface characteristics, and large‐scale field experiments are expensive undertakings. In light of these requirements and shortcomings, satellite observations serve our purposes adequately. The use of satellite data in land surface modeling requires developing a hydrological model with a thin upper layer to be compatible with the nature of the satellite observations and that would evaluate the soil moisture and soil temperature of a thin layer close to the surface. This paper outlines the formulation of a thin layer hydrological model for use in simulating the soil moistures and soil temperatures. This thin layer hydrological model is the first step in our attempt to use microwave brightness temperature data for regional soil moisture estimation. The hydrological model presented here has been calibrated using five years (1980–1984) of daily streamflow data for the Kings Creek catchment. The calibrated parameters are used to validate the daily streamflows for the next 5 year period (1985–1989). The comparison of surface soil moistures and surface temperatures for the period of the Intensive Field Campaigns (IFCs) during the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE) in 1987 is carried out and yields good results. The thin layer hydrological model is coupled with a canopy radiative transfer model and an atmospheric attenuation model to create a coupled soil‐canopy‐atmosphere model in order to study the effect of the vegetation and the soil characteristics on the Special Sensor Microwave Imager (SSM/I) brightness temperatures. The sensitivities of the brightness temperatures to the soil and vegetation is examined in detail. The studies show that increasing leaf area index masks the polarization difference signal originating at the soil surface.

Numerical study of the structure and evolution of a heated planetary boundary layer with a jet

The structure and evolution of a heated, sheared planetary boundary layer (PBL) similar to the one developed on July 11, 1987, during the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) are investigated by a two‐ and a three‐dimensional large eddy simulation (LES) model. The simulated results are utilized to compare with the single Doppler lidar data whose validity, however, has never been thoroughly verified due to insufficient independent observations. In contrast to the traditional research on a buoyancy‐driven, windless convective boundary layer (CBL), the horizontal and vertical domains of this study are designed to be sufficiently large so that the principal physical processes involved in the development of this boundary layer can be successfully simulated. They include (1) large eddies generated by the surface sensible heat flux, (2) internal gravity waves excited in the stable layer due to the lifting mechanism exerted by the rising large eddies, (3) interaction between the waves and the background wind shear, and (4) wave breakdown caused by the convective instability when the flow speed exceeds the phase speed. The mean and statistical properties of this boundary layer turn out to be quite different from those of a CBL. Among them, the most unique feature is that in the stable layer the direction of the momentum flux ( ), which is transported by the gravity waves, is countergradient. The occurrence of this phenomenon, derived by lidar and confirmed by the simulation, is associated with the existence of a critical layer where the Doppler‐shifted frequency vanishes. Under this critical layer the vertical profile of horizontal velocity variance ( ) is found to exhibit a second maximum. The simulated results of potential temperature flux ( ) as well as the potential temperature variance ( ) also imply a second local absolute value maximum in the stable layer. The former is believed to be closely related to the formation of convective instability. Despite the model's ability in simulating the physical processes involved in the FIFE PBL, the large quantitative discrepancy discovered between the model‐generated and the lidar‐extracted statistical properties lead to a consistency check for the latter. It is shown that in the stable layer the magnitudes of the lidar‐observed momentum flux ( ) and the vertical velocity variance ( ) appear to be too strong. Several possible error sources which can contaminate the lidar observations are discussed.

An intercomparison study on models of sensible heat flux over partial canopy surfaces with remotely sensed surface temperature

Using remotely sensed surface temperature to estimate the sensible heat flux over partial canopy covered surfaces, one faces the problem of how the bare soil and plant foliage temperatures contributing to the radiometric surface temperature are related to the turbulent transport of sensible heat across the surface-atmosphere interface. To solve this problem, several sensible heat models, using radiometric surface temperature, have appeared in the literature. In this study, using the observational data from three interdisciplinary field experiments [the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), Monsoon '90 and Washita '92, the performance of four models using average values of their parameters in predicting land surface sensible heat flux was evaluated. By analyzing the sensitivity of the models to common parameters and input variables, reasons for differences in the performances of the models and the potential to improve the agreement with observations have been ascertained. From the comparisons of modeled versus measured sensible heat flux for the different surfaces, the dual-source model in Norman et al. (1995) had the best agreement with its mean absolute percent difference (MAPD) values being similar to the observational accuracy (i.e., ∼ 20%). From the sensitivity analysis the model appears to have the greatest potential for operational applications since it requires relatively few parameters and is not very sensitive to the uncertainty in most of the model parameters. The single-source models in Kustas et al. (1989) and Troufleau et al. (1996) require accurate estimates of the surface roughness z 0m and empirical relationships to account for differences between aerodynamic and radiometric temperature. Therefore, it may be difficult to improve their performance without some independent means of estimating the empirical coefficients and a reliable method for determining z 0m. Estimates from the dual-source model in Lhomme et al. (1994) tend to produce the largest scatter with the observations. This may be related to the fact that the model is more sensitive to variations in most of the parameters common in dual-source models. In addition, its response to high surface-air temperature differences in the sensitivity analysis differs from all other models. Therefore, it may be more difficult to obtain reliable estimates from this model on an operational basis.