Boreal Ecosystem-Atmosphere Study Research Articles

Potentials and Limits of Vegetation Indices With BRDF Signatures for Soil-Noise Resistance and Estimation of Leaf Area Index

Soil-Adjusted Vegetation Index (SAVI) is found to be undesirable to estimate Leaf Area Index (LAI) with heterogeneous canopy structure in low vegetation cover. In this article, three new vegetation indices (VIs), such as Normalized Hotspot-Signature Vegetation Index 2 (NHVI2), Hotspot-Signature Soil-Adjusted Vegetation Index (HSVI), and Hotspot-Signature 2-Band Enhanced Vegetation Index (HEVI2), are proposed for a better quantitative estimation of LAI and soil-noise resistance than with SAVI. To obtain these new indices, the angular index called Normalized Difference between Hotspot and Darkspot (NDHD) is introduced which represents the distribution of foliage in vegetation canopy. The validity of new VIs is statistically verified using simulated data and field measurements. The Discrete Anisotropic Radiative Transfer (DART) model is used to simulate both the homogeneous and heterogeneous canopy for analyzing vegetation isolines behaviors, soil-noise resistance, and LAI estimation. In situ measurements of LAI and bidirectional reflectance factor from the Boreal Ecosystem-Atmosphere Study (BOREAS) are also used to test the robustness of the new VIs for the estimation of LAI. By considering the distribution of the foliage, the accuracy of LAI estimation of SAVI for heterogeneous canopy improved almost 16% using exponential regression analysis. With the improvement of multiangular remote-sensing and Bidirectional Reflectance Distribution Function (BRDF) models in the future, hotspot-signature VIs have the potential to provide a more accurate LAI estimation for heterogeneous canopy in strong soil-noise interference area.

Seasonal change of bidirectional reflectance distribution function in mature Japanese larch forests and their phenology at the foot of Mt. Yatsugatake, central Japan

We constructed a bi-directional reflectance distribution function (BRDF) observation system on a 25-m-high tower surrounded by mature larch forests at the foot of Mt. Yatsugatake, central Japan. The BRDF feature (strong/weak reflections in a backward/forward scattering areas) is related closely to the 3D structure and biophysical parameters of forests. However, because of the difficulty of observations, observational BRDF data of mature forests are scarce, except for those of Boreal Ecosystem –Atmosphere Study (BOREAS). We made BRDF observations 10 times during 2007 to ascertain BRDF characteristics in each season. For comparison to these BRDF data, a semi-empirical BRDF model (Ross–thick Li–sparse kernel model) was introduced. This model can reproduce the BRDF data fairly well under identical solar conditions in each season. Then, seasonal changes of the vegetation structure and possible relations with BRDF were discussed. They are summarized as follows: (1) The forest BRDF changes distinctly and seasonally depending on the phenology. (2) The forest BRDF is influenced primarily by clarity of the geometrical profile on the forest surface, which is affected by shadow. However, the forest BRDF might be influenced by other factors such as the physiological characteristics of leaves and slight change of vegetation structure such as forest floor conditions and leaf angles during summer. (3) Features of forest BRDF must therefore appear during summer when the crown shape is distinctive. Furthermore, BRDF features appear distinctly as seasons progress, e.g., by autumn leaves and defoliation, when the unevenness of forests increases. These findings can promote monitoring of vegetation using multi-angular satellite observations.

Analysis of BRDF and Albedo Retrieved by Kernel-Driven Models Using Field Measurements

The algorithm for Model Bidirectional Reflectance Anisotropies of the Land Surface (AMBRALS) includes a series of kernel-driven bidirectional reflectance distribution function (BRDF) models. Among these models, the RossThick-LiSparse-Reciprocal (RTLSR) model has been selected as the operational MODIS BRDF/Albedo algorithm. With the newly developed LiTransit kernel and Ross kernel with the hotspot effect by Breon, there is a need to further evaluate models' potentials in retrieving land surface properties for user community. In this paper, 16 kernel-driven models in reciprocal form have been analyzed using 70 measurements mainly from ground campaigns of the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) and the Boreal Ecosystem Atmosphere Study (BOREAS). Results show that all models under investigation generally fit the ground measurements with reasonable accuracy—although the “sparse” geometric-optical (GO) kernels appear to present better behaviors compared with the “dense” GO kernels—in combining with volumetric shapes. Estimated albedos from these models show high correlations, while the black-sky albedos (BSAs) present higher correlations in small solar zenith angles than in large ones, indicating that the difference in these kernels may arise from large solar geometry. A further investigation shows that the hotspot effects for these models display a significant discrepancy. Although the additional hotspot factor for Ross kernels significantly improves the hotspot effects, LiTransit kernel can well characterize the hotspot effects in combination with Ross kernels without the hotspot factor. Such an assessment may be helpful in understanding the models' potentials in retrieving vegetation structural characteristics.

Evaluation of Land Surface Scheme SABAE-HW in Simulating Snow Depth, Soil Temperature and Soil Moisture within the BOREAS Site, Saskatchewan

The Soil Atmosphere Boundary, Accurate Evaluation of Heat and Water (SABAE-HW) model is a multilayered, one-dimensional, physically based version of the Canadian Land Surface Scheme (CLASS) and uses the same methodologies as CLASS, version 2.6. SABAE provides an improved interface for groundwater modelling to simulate soil moisture, soil temperature, energy fluxes and snow depth for a wide range of soil and vegetation. This paper reports the results of the first field comparison of SABAE-HW using an extensive ten-year dataset from the Boreal Ecosystem Atmosphere Study (BOREAS) and the Boreal Ecosystem Research and Monitoring Sites (BERMS) project, an area in central Saskatchewan, Canada, rich in terms of hydrological and meteorological data. The model is also independently tested and verified with the Simultaneous Heat and Water (SHAW) model, which is an unsaturated-zone transport model. Two boundary conditions are considered at the bottom of the soil profile: a water table boundary condition and a unit g...

Analysis of diurnal boundary layer development in boreal forests: measurements and simulations

Aims Combining field data analysis and modeling, this study investigates factors influencing the diurnal boundary layer (BL) development in boreal forest. Methods Field data analysis used both air sounding and surface flux measurements collected during the Boreal Ecosystem–Atmosphere Study field campaigns in central Canada. Model study applied a non-local transilient turbulence theory (TTT) to simulate the impact of the heterogeneous boundary conditions together with initial conditions on the BL development at the Candle Lake and Thompson release sites over boreal forests. Boundary conditions were characterized by the integrated surface flux measurements from different forest stands. The lake effect was included in constructing the surface fluxes at Candle Lake release site. Important Findings Analyses of serial upper air sounding data and tower flux data indicate strong linear impacts of surface sensible heat forcing on the diurnal BL development above boreal forests. The regression slopes on the relationship between the BL development and the surface fluxes reflect the influences of initial boundary conditions to the BL developments. Both the modeled and the measured diurnal BLs show that lakes reduce sensible heat flux, leading to a shallower boundary in Candle Lake than in Thompson. Comparison of the model results and field measurements on the BL profiles indicates that the TTT model has the capability to simulate the BL development above boreal forests for sunny, rainfall or cloudy days. This study demonstrates the importance of lake on surface fluxes and BL development. The modeling effort shows the potential to couple the transilient theory with a land surface process model to study land surface and atmosphere interaction in boreal forest.

Assessing the impacts of vegetation heterogeneity on energy fluxes and snowmelt in boreal forests

Aims In the mid- and high-latitude regions, three quarters of the land surface is covered by boreal conifer forests, and snow lasts for 6–8 months of the year. Correctly modeling surface energy balance and snowmelt at mid- and high-latitudes has a significant influence on climate and hydrological processes. However, the heterogeneous and clumped forest structure exerts important control over the radiative energy at the forest floor, which results in large variations of underneath snow cover and snowmelt rate. The goal of this study is to investigate the impact of hierarchically clumped vegetation structure in boreal forest on snowmelt and exchanges of energy and water. Methods We used a simple Clumped Canopy Scheme (CCS) for canopy radiation transfer to characterize the impact of the clumped forest structure on net radiation at the snow surface underneath forests. The CCS was integrated with the Variable Infiltration Capacity macroscale hydrological model (herein referred to as VIC-CCS) to characterize the impact of clumped vegetation structure on surface energy balance and snowmelt during the snow season. A twin simulation, VICCCS and the standard VIC model, was performed to isolate the impact of CCS on the energy and water fluxes and snowmelt rates. The simulation results were compared to in situ measurements at four different forest stands: old aspen forest in the Southern Study Area (SOA), black spruce forests in the Southern and Northern Study Areas (SOBS and NOBS) and fen wetland in the Northern Study Area (NFEN) within the Boreal Ecosystem–Atmosphere Study (BOREAS) region in central Canada during 1994 to1996. Important Findings Simulations showed that the implementation of CCS has reduced incoming long-wave radiation at the underlying snow surface and, thereby, lowered the snowmelt rate. Comparison against ground observations of net radiation and surface flux rates showed a reasonable agreement while demonstrating implementation of CCS can markedly improve model surface energy budget and energy inputs computation for snowmelt. The modeled snowmelt matches reasonably well with observations with root mean square error (RMSE) ranging from 16.51 to 19.81 mm using VIC-CCS versus 29.86 to 32.61 mm for VIC only in the four forest sites. The improvement is the most significant for the deciduous forest (old aspen) site, reducing RMSE by16 mm. This study demonstrates that taking into account the effect of the clumped forest structure in land surface parameterization schemes is critical for snowmelt prediction in the boreal regions.

Evaluation of Snow Albedo in Land Models for Weather and Climate Studies

Abstract Snow albedo plays an important role in land models for weather, climate, and hydrometeorological studies, but its treatment in various land models still contains significant deficiencies. Complementary to previous studies that evaluated the snow albedo as part of an overall land model study, the snow albedo formulations as used in four major weather forecasting and climate models [European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP) “Noah” land model, National Center for Atmospheric Research (NCAR) Community Land Model (CLM3), and NCEP global model] were directly evaluated here using multiyear Boreal Ecosystem–Atmosphere Study (BOREAS) in situ data over grass and forest sites. First, four idealized cases over grass and forest sites were designed to understand better the different albedo formulations in these models. Then the BOREAS data were used to evaluate snow albedo and relevant formulations and to identify deficiencies of each model. Based on these analyses, suggestions that involve only minor changes in parameters or formulations were made to significantly reduce these deficiencies of each model. For the ECMWF land model, using the square root of snow water equivalent (SWE), rather than SWE itself, in the computation of snow fraction would significantly reduce the underestimation of albedo over grass. For the NCEP Noah land model, reducing (increasing) the critical SWE for full snow cover over short (tall) vegetation would reduce the underestimate (overestimate) of snow albedo over the grass (forest) site. For the NCAR CLM3, revising the coefficient used in the ground snow-fraction computation would substantially reduce the albedo underestimation over grass. For the albedo formulations in the NCEP global model, replacing the globally constant fresh snow albedo by the vegetation-type-dependent Moderate-Resolution Imaging Spectroradiometer (MODIS) maximum snow albedo would significantly improve the overestimation of model albedo over forest.

Improving the estimation of leaf area index by using remotely sensed NDVI with BRDF signatures

A new vegetation index, the Normalized Hotspot-signature Vegetation Index (NHVI), is proposed for a better quantitative estimation of leaf area index (LAI) than with the remotely sensed normalized difference vegetation index (NDVI), especially in the boreal forest. To obtain this new index, the Hotspot–Dark-spot index (HDS) (Lacaze et al., 2002) was introduced. HDS is calculated by the difference between the strongest vector (hotspot) and the weakest vector (dark-spot) of bi-directional reflectance, a given tract of vegetation returns in the reflecting solar position, and the geometric structure of the vegetation canopy, which are poorly represented by NDVI alone. The validity of NHVI was statistically tested using two field data sets of multi-angular observations and LAI from the boreal forests of Canada; one set was our own observations, and the other was from the Boreal Ecosystem–Atmosphere Study (BOREAS). The range of linear correspondence of NHVI with LAI is much wider than that of NDVI alone, indicating significant representation of leaf biomass in the canopy geometry captured by HDS. With the technical innovation of multi-angular remote-sensing and kernel-driven models in the future, this index has the potential to provide a more accurate evaluation of regional and global LAIs.

Multiple Scattering Within the FLAIR Model Incorporating the Photon Recollision Probability Approach

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In this paper, a combined approach based on the adding method is incorporated into the four-scale linear model for anisotropic reflectance (FLAIR) to enhance the description of the spectrally dependent multiple-scattered radiation field of a forest canopy. The proposed scheme is based on the decomposition of the multiple-scattered radiation field into two parts. The first part deals with multiple scattering within the canopy, considering a competently black soil, and the second part deals with multiple scattering between the canopy and the background. Such advances to radiative transfer modeling are required to better exploit the potential of hyperspectral remote sensing for monitoring canopy biochemical indicators such as chlorophyll concentration and equivalent water content. The validation was performed using the multiangular data sets obtained by the airborne sensor POLarization and Directionality of the Earth's Reflectances (POLDER) during the BOReal Ecosystem–Atmosphere Study (BOREAS) campaign of 1994. The results indicate that this approach is well suited to the FLAIR model. It is also demonstrated that the multiple-scattering problem can be parameterized by a limited number of architectural parameters and the leaf scattering coefficient. </para>

Modeling snow accumulation and ablation processes in forested environments

The effects of forest canopies on snow accumulation and ablation processes can be very important for the hydrology of midlatitude and high‐latitude areas. A mass and energy balance model for snow accumulation and ablation processes in forested environments was developed utilizing extensive measurements of snow interception and release in a maritime mountainous site in Oregon. The model was evaluated using 2 years of weighing lysimeter data and was able to reproduce the snow water equivalent (SWE) evolution throughout winters both beneath the canopy and in the nearby clearing, with correlations to observations ranging from 0.81 to 0.99. Additionally, the model was evaluated using measurements from a Boreal Ecosystem‐Atmosphere Study (BOREAS) field site in Canada to test the robustness of the canopy snow interception algorithm in a much different climate. Simulated SWE was relatively close to the observations for the forested sites, with discrepancies evident in some cases. Although the model formulation appeared robust for both types of climates, sensitivity to parameters such as snow roughness length and maximum interception capacity suggested the magnitude of improvements of SWE simulations that might be achieved by calibration.

Boreal forest mapping at the BOREAS study area using seasonal optical indices sensitive to plant pigment content

In this study, forest vegetation classification was investigated based on seasonal variation of pigments as inferred from visible and near-infrared spectral bands. This analysis was carried out on data collected over the southern study area of the Boreal Ecosystem-Atmosphere Study (BOREAS) with the Compact Airborne Spectrographic Imager (casi) in May and July 1994 and with the medium-resolution imaging spectrometer (MERIS) in May and August 2003. Three modified normalized difference vegetation indices (mNDVIs), which are sensitive to relative proportions among pigments and pigment content, and a red-edge spectral parameter, the wavelength at the reflectance minimum (λ0), were used. Accuracy assessments of the derived land cover maps were performed using a forest inventory map provided by the Saskatchewan Environment and Resource Management Forestry Branch Inventory Unit (SERM–FBIU). The forest vegetation classification using seasonal optical indices (mNDVIs and λ0), as derived from the casi data in May and July, shows an overall accuracy of 84% for all cover types identified, namely dry conifer, wet conifer, mixed stands, aspen, fen, and the disturbed and regenerated area. The classification results also demonstrate that classification using reflectance parameters sensitive to pigment absorption features outperforms that using the reflectance itself. In addition, the classification using seasonal information is better than that using information obtained from a single date, and the spatial patterns were consistent with those achieved using multidate MERIS imagery. The forest vegetation classification using seasonal changes in optical indices (mNDVIs and λ0) derived from the MERIS imagery in May and August revealed a reasonably high overall classification accuracy (72%) for all vegetation cover types identified, namely conifer, mixed stands, and fen.

Physically based inversion modeling for unsupervised cluster labeling, independent forest classification, and LAI estimation using MFM-5-Scale

Unsupervised clustering is important for regional- to national-scale forest inventories where supervised training data are impractical or unavailable. However, labeling clusters in terms of land-cover classes can be labour intensive and problematic, and clustering and related methods do not provide biophysical-structural information (BSI). Canopy reflectance models such as 5-Scale are powerful forest remote sensing tools; however, 5-Scale can only be run in forward mode and is not invertible to obtain the required forest information. This problem was solved using multiple-forward-mode (MFM) coupled with 5-Scale to enable MFM-5-Scale inversion of land cover and BSI using a look-up table (MFM-LUT) approach that matches satellite image reflectance values with modeled reflectance values that have associated land cover and BSI, such as density, leaf area index (LAI), and crown dimensions, as well as subpixel-scale component fractions. MFM requires no training data or a priori BSI and can optionally be stratified (generalized) by species, structural, hierarchical, mixed forest, and other class definitions. In this paper, MFM-5-Scale was used with Landsat thematic mapper (TM) imagery at the Boreal Ecosystem-Atmosphere Study (BOREAS) southern study area (SSA) modeling subarea (MSA) in Saskatchewan, Canada. MFM-5-Scale was used to label unsupervised cluster sets (n = 17 and 97) from a previous land-cover classification by progressive generalization (CPG), with the best results obtained from independent, stand-alone MFM classification (87%, 76%, and 71% for the three hierarchies of 16 forest type, species, and density classes) validated against the provincial (SERM) forest inventory map and also compared with a standard maximum likelihood (ML) classification. Further, MFM-5-Scale estimated LAI at 24 BOREAS plots within ±0.57 LAI compared with ground-based tracing radiation and architecture of canopies (TRAC) LAI validation data. BSI is not provided by CPG clustering or ML. Based on this and other studies, we conclude that MFM provides an inversion modeling context for sophisticated forest radiative transfer models to retrieve a higher level of land cover and BSI, with detailed LUTs providing a rich set of forest information suitable for query, analysis, and follow-on simulation studies. These methods can augment existing regional- to national-scale remote sensing based inventories by providing a robust cluster labeling and BSI capability or can provide stand-alone capabilities over a variety of applications and scales.

Effect of stability on mixing in open canopies

In open canopies, the within-canopy flux from the ground surface and understory can account for a significant fraction of the total flux above the canopy. Here, “open” canopies refer to sufficient spacing between vegetation elements to allow significant clear-sky radiative heating and cooling of the ground or understory surface, which in turn significantly influences the subcanopy turbulence. This study incorporates the important influence of within-canopy stability on turbulent mixing and subcanopy fluxes into a first-order closure scheme. Toward this goal, we analyze within-canopy eddy-correlation data from the old aspen site in the Boreal ecosystem–atmosphere study (BOREAS) and a mature ponderosa pine site in Central Oregon, USA. A formulation of within-canopy transport is framed in terms of a stability-dependent eddy diffusivity, which approaches Monin–Obukhov similarity theory above the canopy roughness sublayer. The new simple formulation for the subcanopy is an improvement upon the usual neglect of the influence of stability on turbulent mixing. However, frequent well-defined cold air drainage within the pine subcanopy inversion reduces the utility of simple models for nocturnal transport. Other shortcomings of the formulation are discussed.

A comparison of methane flux in a boreal landscape between a dry and a wet year

We used field measurements of methane (CH4) flux from upland and wetland soils in the Northern Study Area (NSA) of BOREAS (BOReal Ecosystem‐Atmosphere Study), near Thompson, Manitoba, during the summers of 1994 and 1996 to estimate the overall CH4 emission from a 1350 km2 landscape. June–September 1994 and 1996 were both drier and warmer than normal, but summer 1996 received 68 mm more precipitation than 1994, a 40% increase, and had a mean daily air temperature 0.6°C warmer than 1994. Upland soils consumed CH4 at rates from 0 to 1.0 mg m−2 d−1, with small spatial and temporal variations between years, and a weak dependence on soil temperature. In contrast, wetlands emitted CH4 at seasonal average rates ranging from 10 to 350 mg CH4 m−2 d−1, with high spatial and temporal variability, and increased an average of 60% during the wetter and warmer 1996. We used Landsat imagery, supervised classification, and ground truthing to scale point CH4 fluxes (&lt;1 m2) to the landscape (&gt;1000 km2). We performed a sensitivity analysis for error terms in both areal coverage and CH4 flux, showing that the small areas of high CH4 emission (e.g., small ponds, graminoid fens, and permafrost collapse margins) contribute the largest uncertainty in both flux measurements and mapping. Although wetlands cover less than 30% of the landscape, areally extrapolated CH4 flux for the NSA increased by 61% from 10 to16 mg CH4 m−2 d−1 between years, entirely attributed to the increase in wetland CH4 emission. We conclude that CH4 fluxes will tend to be underestimated in areas where much of the landscape is covered by wetlands. This is due to the large spatial and temporal variability encountered in chamber‐based measurements of wetland CH4 fluxes, strong sensitivity of wetland CH4 emission to small changes in climate, and because most remote sensing images do not adequately identify small areas of high CH4 flux.

Effects of vegetation canopy processes on snow surface energy and mass balances

This paper addresses the effects of canopy physical processes on snow mass and energy balances in boreal ecosystems. We incorporate new parameterizations of radiation transfer through the vegetation canopy, interception of snow by the vegetation canopy, and under‐canopy sensible heat transfer processes into the Versatile Integrator of Surface and Atmosphere (VISA) and test the model results against the Boreal Ecosystem‐Atmosphere Study (BOREAS) data observed at South Study Area, Old Jack Pine. A modified two‐stream radiation transfer scheme that accounts for the three‐dimensional geometry of vegetation accurately simulates the transferring of solar radiation through the vegetation canopy when the leaf and stem area index is reduced to match the observed. VISA produces higher‐than‐observed surface albedo in wintertime. Implementation of a snow interception model that explicitly describes the loading and unloading of snow and the melting and refreezing of snow on the canopy into VISA reduces the fractional snow cover on the canopy and the surface albedo. VISA overestimates the downward sensible heat fluxes from the canopy to the snow surface, which leads to earlier snow ablation and a shallower snowpack than the observed. Explicitly including a canopy heat storage term in the canopy energy balance equation decreases the spuriously large amplitude of the diurnal canopy temperature variation and reduces the excessive daytime sensible heat flux from the canopy downward to the snow surface. Sensitivity tests reveal that the turbulent sensible heat flux below the vegetation canopy strongly depends on the canopy absorption coefficient of momentum. During spring the daytime temperature difference between the snow surface and the vegetation canopy forms a strongly stable atmospheric condition, which results in a larger absorption coefficient of momentum and a weak turbulent sensible heat flux. The modeled excessive downward sensible heat flux from the vegetation canopy to the snow surface is considerably reduced through the stability correction to the canopy absorption coefficient of momentum.

Distributed hydrological model for mapping evapotranspiration using remote sensing inputs

A distributed hydrological model [Wigmosta, M.S., Vail, L.W., Lettenmaier, D.P., 1994. A distributed hydrology-vegetation model for complex terrain. Water Resource Research 30 (6), 1665–1679] is further developed to simulate the detailed spatial and temporal variation patterns of evapotranspiration (ET) around a flux tower site. In addition to meteorological, topographical and soil data, the model utilizes optical remote sensing data (Landsat TM at 30 m resolution) to characterize the distributions of vegetation types and the leaf area index (LAI). The use of LAI allows process-based modeling of major hydrological processes including transpiration, precipitation interception, and evaporation from vegetation and soil. Water flows within and between five strata (overstore, understore, moss/litter, soil unsaturated zone, and soil saturated zone) are modeled on a daily basis. A moving window of nine pixels is used to consider the lateral subsurface flow. The model is applied to a small watershed of dimension of about 16 km×12 km in Saskatchewan, Canada. The temporal variations of simulated ET are compared with eddy-covariance ET measurements over a black spruce stand located within the watershed. The stand was the Old Black Spruce in the Southern Study Area during the Boreal Ecosystem-Atmosphere Study (BOREAS) in 1994. Although the black spruce site is located in a flat area with less than 1.5 m topographical variation within 150 m of the flux tower, there was about 10.5 mm water loss through saturated subsurface flow during the growing season of 1994, accounting for 5.7% of the rainfall in same period. Even though the watershed studied had gentle terrain variations, the topography had considerable influence not only on the water table but also on the soil moisture and saturated water redistribution. This suggests the importance of modeling hydrological processes as influenced by topography in mapping ET.

Modeling Snow Depth for Improved Simulation of Snow–Vegetation–Atmosphere Interactions

The presence of snow and its relationship to surrounding vegetation significantly impacts the surface energy balance. For accurate atmospheric model simulations, the degree to which a snowpack can cover vegetation must be realistically represented. Both vegetation height and snow depth must be reasonably known to determine the amount of masking. The Regional Atmospheric Modeling System/Land Ecosystem‐Atmosphere Feedback, version two (RAMS/ LEAF-2) snow model was modified to simulate snow depth in addition to snow water equivalent and was driven offline with observed atmospheric forcing data. The model was run for five of the Boreal Ecosystem‐Atmosphere Study (BOREAS) surface mesonet stations over the 1995/96 winter. The time evolution of simulated snow depth was compared with the observed snow depth. Averaged over the winter, the modeled snow depth at the four low-wind stations was within 0.09 m of the observations, and the average percent error was 27%, while the one wind-blown station was considerably worse. The average depth error at all five stations was 60.08 m. This is shown to be sufficient to reasonably account for the surface energy balance effects of vegetation protruding through the snow.

The effects of sampling resolution on the surface albedos of dominant land cover types in the North American boreal region

The central role that land surface albedo ( α) plays in the physical climate system makes it a key component of climate and ecosystem models. However, this parameter remains one of the largest radiative uncertainties associated with modelling attempts. Uncertainty occurs because models commonly prescribe albedo using in situ observations, which are rarely sufficiently dense to accurately characterize albedo at a regional scale. This is especially problematic over seasonally snow-covered landscapes such as the boreal forest. The aims of this study are to (a) analyze and compare the local- and regional-scale albedo characteristics of the dominant land cover types found within the North American boreal region, (b) assess the effects of snow cover on these patterns, and (c) quantify the potential bias that can result from using local-scale observations to describe surface albedos across larger geographical extents. Our study is based on local-scale in situ observations and regional-scale satellite (Geostationary Operational Environmental Satellite—GOES) measurements that were collected as part of the Boreal Ecosystem-Atmosphere Study (BOREAS). Our results show (a) that the albedo patterns among land cover types are generally consistent at local and regional scales, (b) that snow cover not only increases the albedo of all cover types, but also their sensitivities to changes in solar zenith angle, and (c) that weekly averaged in situ observations provide a reasonable characterization of regional-scale albedo when under snow-free conditions, but a poor characterization when snow is present. Land cover albedo characteristics are caused by canopy properties that influence within-canopy shadowing. The disparity between in situ albedo observations and those collected over low-density needleleaf forest are particularly a concern because this cover type comprises a significant proportion of the boreal region, and its mis-specification in climate models could lead to large errors in energy balance. Further studies should focus on reducing the disparity between albedo data sets over snow-covered surfaces. They should also consider the effects of diffuse radiation, as well as finer time scales, on the above relationships.

Snow water equivalent retrieval in a Canadian boreal environment from microwave measurements using the HUT snow emission model

Snow water equivalent (SWE) is a critical parameter for climatological and hydrological studies over northern high-latitude areas. In this paper, we study the usability of the Helsinki University of Technology (HUT) snow emission model for the estimation of SWE in a Canadian boreal forest environment. The experimental data (airborne passive microwave and ground-based data) were acquired during the Boreal Ecosystem-Atmosphere Study winter field campaign held in February 1994 in Central Canada. Using the experimental dataset, surface brightness temperatures at 18 and 37 GHz (vertical polarization) were simulated with the HUT snow emission model and compared to those acquired by the airborne sensors. The results showed an important underestimation at 37 GHz (-27 K) and an overestimation at 18 GHz (10 K). In this paper, we demonstrate that the errors in the model simulations are due mainly to the extinction coefficient modeling, which is a function of snow grain size. Therefore, we propose a new semiempirical function for the extinction coefficient, based on an empirical correction to the Rayleigh scattering expression. Results presented in this paper show that the proposed function improves the HUT model accuracy to predict brightness temperature in the experimental context considered, with a mean error of /spl plusmn/5 K and /spl plusmn/9 K, respectively, at 18 and 37 GHz, and a negligible bias (less than 4 K) in both cases. These errors are comparable in magnitude to the accuracy of the radiometers used during the airborne flights. SWE was retrieved using the modified HUT snow emission model based on an iterative inversion technique. SWE was estimated with a mean error of /spl plusmn/10 mm and a negligible bias. Only a rough knowledge of mean snow grain size /spl phi/~ was required in the inversion procedure. The effects of possible errors on mean snow grain size /spl phi/~ are presented and discussed.

Aerosol optical depth spatio-temporal characterization over the Canadian BOREAS domain

A complete set of Advanced Very High Resolution Radiometer (AVHRR) data (75 images) is used to retrieve aerosol optical depth (AOD) over dense vegetation and over lake water in the visible AVHRR channel. The present approach for remote sensing of aerosols from the National Oceanic and Atmospheric Administration (NOAA)-11 AVHRR sensor is based on the detection of atmospherically dominated signals over dark surface covers such as dense dark vegetation (DDV). Such targets were identified using the reflective portion of the middle-wave AVHRR channel 3 signal. When a fixed DDV surface reflectance is subtracted from the observed reflectance after correction for all other atmospheric effects, the remaining part, which is due to aerosols, is inverted to derive aerosol optical thickness using a look-up table (LUT) similar to that used in water surface inversion. The algorithm was applied to the daily afternoon NOAA-11 AVHRR (1 km×1 km) data acquired from the end of May to mid-August 1994 over the Canadian 1000 km×1000 km Boreal Ecosystem Atmosphere Study (BOREAS) domain. A validation analysis using five ground-based Sun photometers within the studied area shows the good performance of the retrieval algorithm. The approach allows detailed analysis of the AOD spatio-temporal behaviour at the regional scale useful for climate and transport model validation.