Robert J. Gurney

Area‐averaged surface fluxes and their time‐space variability over the FIFE experimental domain

The underlying mean and variance properties of surface net radiation, soil heat flux, and sensible-latent heat fluxes are examined over the densely instrumented grassland region encompassing the First ISLSCP Field Experiment (FIFE). Twenty-two surface flux stations at 20 sites were deployed during the four 1987 intensive field campaigns (IFCs). Flux variability is addressed together with the problem of scaling up to area-averaged fluxes. Successful parameterization of area-averaged fluxes in atmospheric models is based on accounting for internal spatial and temporal scales correctly. Mean and variance properties of fluxes are examined in both daily and diurnally averaged frameworks. Results are compared and contrasted for clear and cloudy situations and checked for the influence of surface-induced biophysical controls (burn and grazing treatments) and topographic controls (slope factors and aspect ratios). Examination of the sensitivity of domain-averaged fluxes to different averaging procedures demonstrates that this may be an important consideration. The results reveal six key features of the 1987 surface fluxes: (1) cloudiness variability and ample rainfall throughout the growing season led to near-consistency in flux magnitudes during the first three IFCs; (2) burn treatment, grazing conditions, and topography have clearly delineated influences on the diurnal cycle flux amplitudes but do not alter the evaporative fraction significantly; (3) cloudiness is the major control on flux variability in terms of both mean and variance properties but has little impact on the Bowen ratio or evaporative fraction; (4) spatial weighting of fluxes based on a biophysicaltopographical cross stratification generates a measurable bias with respect to straight arithmetic averaging (up to 20 W m−2 in available heating); (5) structure function analysis demonstrates significant underlying spatial autocorrelation structure in the fluxes, but the observed distance dependence is due to cloudiness controls, not surface controls; (6) Monte Carlo analysis of high resolution vegetation indices obtained from SPOT satellite measurements suggest that the mean domain amplitudes of the diurnal sensible and latent heat flux cycles can be biased up to 30–40 W m −2 by repositioning the 20 site locations within the experimental domain.

Surface flux measurements in FIFE: An overview

In 1987 the Surface Flux Group of the first ISLSCP Field Experiment (FIFE) operated 22 stations at 20 sites. In 1989, 13 sites were instrumented. A variety of sensors were employed to calculate the fluxes of mass and energy. An effort was made throughout the FIFE campaign to compare sensors. A series of papers in this special issue present these group studies and efforts. These papers principally report the 1987 campaign, although two papers report station intercomparison during 1989. Additional papers examine the time-space variability of heat, moisture, and momentum fluxes, as well as analyses of the properties of the CO2 fluxes and their relationships to water stress. In this overview paper we describe the basic methodologies of the measurements, provide details on the sensor systems used by members of the Surface Flux Group, and provide a summary of the flux articles appearing in this special issue.

Calibrating a soil water and energy budget model with remotely sensed data to obtain quantitative information about the soil

A soil water energy and transpiration model (SWEAT) coupled with a microwave emission model (MICRO-SWEAT) was used to predict the microwave brightness temperature of both bare and corn plots during a drying cycle. The predicted microwave brightness temperatures compared favorably to measurements made with an L band (21 cm, 1.4 GHz) passive microwave radiometer. In addition, SWEAT successfully modeled time series of soil water content and soil temperature. The modeled brightness temperature for the bare soil was most sensitive to the parameters describing the soil water retention and conductivity characteristics. These were predicted by varying each parameter in turn until there was a minimum between the measured and modeled brightness temperature. The predicted parameters were in agreement with the measured values to within the experimental error. The microwave brightness temperatures estimated for the corn soil were sensitive to the vegetation parameters as well as to the soil hydraulic properties.

Using a modeling approach to predict soil hydraulic properties from passive microwave measurements

A soil water and energy budget model coupled with a microwave emission model (MICRO-SWEAT) was used to predict the diurnal courses of soil surface water content and microwave brightness temperatures during a number of drying cycles on soils of contrasting texture that were either cropped or bare. The parameters describing the soil water retention and conductivity characteristics [saturated hydraulic conductivity, air entry potential, bulk density, and the exponent (b) describing the slope of the water release curve] had a strong influence on the modeled bare-soil microwave brightness temperatures. These parameters were varied until the error between the remotely sensed and modeled brightness temperatures was minimized, leading to their predicted values. These predictions agreed with the measured values to within the experimental error. The modeled brightness temperature for a soybean-covered soil was sensitive to some of the vegetation parameters (particularly to the optical depth), in addition to the soil hydraulic properties. Preliminary findings suggest that, given an independent estimate of the vegetation parameters, it may still be possible to estimate the soil hydraulic properties under a moderate vegetation canopy.

Characterizing errors in airborne laser altimetry data to extract soil roughness

Airborne laser altimetry has the potential to make frequent detailed observations that are important for many aspects of studying land surface processes. However, the uncertainties inherent in airborne laser altimetry data have rarely been well measured. Uncertainty is often specified as generally as 20 cm in elevation and 40 cm planimetric. To better constrain these uncertainties, we present an analysis of several datasets acquired specifically to study the temporal consistency of laser altimetry data and, thus, assess its operational value. The error budget has three main components, each with a time regime. For measurements acquired less than 50 ms apart, elevations have a local standard deviation in height of 3.5 cm, enabling the local measurement of surface roughness of the order of 5 cm. Points acquired seconds apart acquire an additional random error due to differential geographic positioning system fluctuation. Measurements made up to an hour apart show an elevation drift of 7 cm over a half hour. Over months, this drift gives rise to a random elevation offset between swathes, with an average of 6.4 cm. The root mean square planimetric error in point location was derived as 37.4 cm. We conclude by considering the consequences of these uncertainties on the principle application of laser altimetry in the U.K. intertidal zone monitoring.

A new Snow-SVAT to simulate the accumulation and ablation of seasonal snow cover beneath a forest canopy

A new snow-soil-vegetation-atmosphere transfer (Snow-SVAT) scheme, which simulates the accumulation and ablation of the snow cover beneath a forest canopy, is presented. The model was formulated by coupling a canopy optical and thermal radiation model to a physically based multi-layer snow model. This canopy radiation model is physically based yet requires few parameters, so can be used when extensive in situ field measurements are not available. Other forest effects such as the reduction of wind speed, interception of snow on the canopy and the deposition of litter were incorporated within this combined model, SNOWCAN, which was tested with data taken as part of the Boreal Ecosystem-Atmosphere Study (BOREAS) international collaborative experiment. Snow depths beneath four different canopy types and at an open site were simulated. Agreement between observed and simulated snow depths was generally good, with correlation coefficients ranging between r(2) = 0.94 and r(2) = 0.98 for all sites where automatic measurements were available. However, the simulated date of total snowpack ablation generally occurred later than the observed date. A comparison between simulated solar radiation and limited measurements of sub-canopy radiation at one site indicates that the model simulates the sub-canopy downwelling solar radiation early in the season to within measurement uncertainty.

A sensitivity analysis of soil moisture retrieval from the tau-omega microwave emission model

The potential of the /spl tau/--/spl omega/ model for retrieving the volumetric moisture content of bare and vegetated soil from dual-polarization passive microwave data acquired at single and multiple angles is tested. Measurement error and several additional sources of uncertainty will affect the theoretical retrieval accuracy. These include uncertainty in the soil temperature, the vegetation structure, and consequently its microwave single-scattering albedo, and uncertainty in soil microwave emissivity based on its roughness. To test the effects of these uncertainties for simple homogeneous scenes, we attempt to retrieve soil moisture from a number of simulated microwave brightness temperature datasets generated using the /spl tau/--/spl omega/ model. The uncertainties for each influence are estimated and applied to curves generated for typical scenarios, and an inverse model used to retrieve the soil moisture content, vegetation optical depth, and soil temperature. The effect of each influence on the theoretical soil moisture retrieval limit is explored, the likelihood of each sensor configuration meeting user requirements is assessed, and the most effective means of improving moisture retrieval indicated.

Measurement of canopy geometry characteristics using LiDAR laser altimetry: a feasibility study

Airborne scanning laser altimetry offers the potential for extracting high-resolution vegetation structure characteristics for monitoring and modeling the land surface. A unique dataset is used to study the sensitivity of laser interception profiles and laser-derived leaf area index (LAI) to assumptions about the surface structure and the measurement process. To simulate laser interception, one- and three-dimensional (3-D) vegetation structure models have been developed for maize and sunflower crops. Over sunflowers, a simple regression technique has been developed to extract laser-derived LAI, which accounts for measurement and model biases. Over maize, a 3-D structure/interception model that accounts for the effects of the laser inclination angle and detection threshold has enabled the fraction of radiation reaching the ground surface to be modelled to within 0.5% of the observed fraction. Good agreement was found between modelled and measured profiles of laser interception with a vertical resolution of 10 cm.

The use of GPS measurements for water vapor determination

Abstract A workshop on the use of Global Positioning System (GPS) measurements in weather and climate with emphasis on water vapor determination, was organized by the National Environmental Research Councils (NERC) Environmental Systems Science Centre (ESSC), at the University of Reading, Reading, United Kingdom, and took place there 29–31 August 2001. This paper gives a broad overview and general background of the use of GPS data for weather and climate. It outlines the objectives of the workshop and presents ongoing national, regional, and international activities both for ground-based and satellite-based systems. This includes work in the United States, China, and Japan, and different European efforts, including activities under European Community programs. Data assimilation of GPS data for weather prediction and climate is discussed as are ways in which to develop GPS-based systems to become an integrated part of the World Weather Watch. This includes ways of systematically using GPS data from the in...

The Radiative Effect of a Fir Canopy on a Snowpack

Abstract Models of snow processes in areas of possible large-scale change need to be site independent and physically based. Here, the accumulation and ablation of the seasonal snow cover beneath a fir canopy has been simulated with a new physically based snow–soil vegetation–atmosphere transfer scheme (Snow-SVAT) called SNOWCAN. The model was formulated by coupling a canopy optical and thermal radiation model to a physically based multilayer snow model. Simple representations of other forest effects were included. These include the reduction of wind speed and hence turbulent transfer beneath the canopy, sublimation of intercepted snow, and deposition of debris on the surface. This paper tests this new modeling approach fully at a fir site within Reynolds Creek Experimental Watershed, Idaho. Model parameters were determined at an open site and subsequently applied to the fir site. SNOWCAN was evaluated using measurements of snow depth, subcanopy solar and thermal radiation, and snowpack profiles of tempera...