George R. Diak

Estimating fluxes on continental scales using remotely sensed data in an atmospheric-land exchange model

A simple model of energy exchange between the land surface and the atmospheric boundary layer, driven by input that can be derived primarily through remote sensing, is described and applied over continental scales at a horizontal resolution of 10 km. Surface flux partitioning into sensible and latent heating is guided by time changes in land surface brightness temperatures, which can be measured from a geostationary satellite platform such as the Geostationary Operational Environmental Satellite. Other important inputs, including vegetation cover and type, can be derived using the Normalized Difference Vegetation Index in combination with vegetation and land use information. Previous studies have shown that this model performs well on small spatial scales, in comparison with surface flux measurements acquired during several field experiments. However, because the model requires only a modicum of surface-based measurements and is designed to be computationally efficient, it is particularly well suited for regional- or continental-scale applications. The input data assembly process for regional-scale applications is outlined. Model flux estimates for the central United States are compared with climatological moisture and vegetation patterns, as well as with surface-based flux measurements acquired during the Southern Great Plains (SGP-97) Hydrology Experiment. These comparisons are quite promising.

Surface flux estimation using radiometric temperature: A dual‐temperature‐difference method to minimize measurement errors

Surface temperature serves as a key boundary condition that defines the partitioning of surface radiation into sensible and latent heat fluxes. Surface brightness temperature measurements from satellites offer the unique possibility of mapping surface heat fluxes at regional scales. Because uncertainties in satellite measurements of surface radiometric temperature arise from atmospheric corrections, surface emissivity, and instrument calibrations, a number of studies have found significant discrepancies between modeled and measured heat fluxes when using radiometric temperature. Recent research efforts have overcome these uncertainties and in addition have accounted for the difference between radiometric and aerodynamic temperature by considering soil and vegetative-canopy aerodynamic resistances. The major remaining obstacle to using satellite data for regional heat flux estimation is inadequate density of near-surface air temperature observations. In this paper we describe a simple, operational, double-difference approach for relating surface sensible heat flux to remote observations of surface brightness temperature, vegetative cover and type, and measurements of near-surface wind speed and air temperature from the synoptic weather network. A double difference of the time rate of change in radiometric and air temperature observations is related to heat flux. This double-difference approach reduces both the errors associated with deriving a radiometric temperature and with defining meteorological quantities at large scales. The scheme is simpler than other recent approaches because it requires minimal ground-based data and does not require modeling boundary layer development. The utility of this scheme is tested with ground-based radiometric temperature observations from several arid and subhumid climates with a wide range of vegetative cover and meteorological conditions.

Application of Geostatistics to Characterize Leaf Area Index (LAI) from Flux Tower to Landscape Scales Using a Cyclic Sampling Design

AbstractAccurate characterization of leaf area index (LAI) is required to quantify the exchange of energy, water, and carbon between terrestrial ecosystems and the atmosphere. The objective of this study was to use a cyclic sampling design to compare the spatial patterns of LAI of the dominant terrestrial ecosystems that comprised the area around the 447-m WLEF television tower, equipped with an eddy flux system, near Park Falls, Wisconsin, USA. A second objective was to compare the efficiency of cyclic, random, and uniform sampling designs in terms of the precision of spatial information derived per unit sampling effort. The vegetation surrounding the tower was comprised (more than 80%) of four major forest cover types: forested wetlands, upland aspen forests, upland northern hardwood forests, and upland pine forests, and a fifth, nonforested cover type, grass (open meadow). LAI differed significantly among the five cover types and averaged 3.45, 3.57, 3.82, 3.99, and 1.14 for northern hardwoods, aspen, forested wetlands, upland conifers, and grass, respectively. The cyclic sampling design maximized information about the variance of vegetation characteristics of the heterogeneous landscape and decreased by 60% the number of plots needed to obtain the same confidence interval width using a random sampling design. The range of spatial autocorrelation for LAI was 147 m, but it was decreased to 117 m when vegetation cover was included as a covariate. The cyclic sampling design has several important advantages over other sampling designs. The cyclic sampling design increased the sampling efficiency by optimizing the placement of plots so they were distributed more efficiently for geostatistical analyses such as semi-variograms, correlograms, and spatial regression and can incorporate covariates (for example, vegetation cover, soil properties, and so on) that may explain the sources of spatial patterns. The cyclic sampling design was used to derive a spatial map of LAI and the average LAI for the 3 × 2 km area centered on the flux tower was 3.51 ± 0.89 (with a minimum of 0 and a maximum of 6.35). Airborne and satellite reflectance data have also been used to characterize LAI, but in this region, and many other forests of the world, remotely sensed vegetation indexes saturate in forests with an LAI greater than 3–5. The cyclic sampling design also provides a general ecological sampling approach that can be used at multiple scales.

Estimating Land Surface Energy Budgets From Space: Review and Current Efforts at the University of Wisconsin—Madison and USDA–ARS

Abstract Since the advent of the meteorological satellite, a large research effort within the community of earth scientists has been directed at assessing the components of the land surface energy balance from space. The development of these techniques from first efforts to the present time are reviewed, and the integrated system used to estimate the radiative and turbulent land surface fluxes is described. This system is now running in real time over the continental United States at a resolution of 10 km, producing daily and time-integrated flux components.

Improvements to a Simple Physical Model for Estimating Insolation from GOES Data

Abstract The simple physical model to estimate surface insolation from GOES data (described in Gautier et al., 1980) has been improved through some modifications to existing physics (Rayleigh scattering and water vapor absorption), and also the inclusion of ozone absorption, previously neglected. An empirical correction for clouds smaller than the GOES sensor field-of-view has also been introduced. The resulting model is more physically realistic than the old one and requires no additional computer time. Tests indicate that with minimal tuning, the error in daily insulation estimates has been reduced by ∼1% compared to the old model. Removal of systematic error resulted in an additional 0.2% improvement.

Improvements to models and methods for evaluating the land-surface energy balance and ‘effective’ roughness using radiosonde reports and satellite-measured ‘skin’ temperature data

Abstract In this paper, we expand on a technique developed previously which uses radiosonde measurements of the daytime change of the height of the planetary boundary layer in combination with geostationary satellite measurements of surface skin temperature to evaluate the energy balance and an ‘effective’ roughness of the land surface. The improvements described here are primarily designed to increase the amount of usable data produced by the system by expanding the range of circumstances under which measurements can be taken. Previously, to make surface evaluations it was necessary that the local time-change of the surface temperature and PBL structure be dominated by the diurnal surface flux exchanges. In this paper, we test several techniques to compensate for the effects of horizontal and vertical temperature advection and vertical motions above the planetary boundary layer. The improved techniques and the sensitivities of the determination of the surface energy balance and effective roughness to advection and vertical motions are investigated in a case study including 3 days of data for locations in the Midwest and Great Plains areas of continental USA in the summers of 1987 and 1988.

GOES surface insolation to estimate wetlands evapotranspiration

Incoming solar radiation derived from GOES-8 satellite observations, in combination with local meteorological measurements, were used to model evapotranspiration from a wetland. The wetland experiment was conducted in the Paynes Prairie Preserve, North Central Florida during a growing season characterized by significant convective activity. The satellite solar radiation measurements generally agreed with pyranometer data gathered at the site. The satellite net radiation estimates were in good agreement with the 30-min averages of measured net radiometer data. Satellite derived net radiation estimates were used in the Penman‐ Monteith and Priestley ‐ Taylor models to calculate evapotranspiration. The calculated instantaneous evaporative fluxes were in good agreement with 30-min average ground-based eddy correlation system measurements. The daily averages of modeled evapotranspiration were in very good agreement ðr 2 ¼ 0:90Þ with reference eddy flux

Validation of GOES-Based Insolation Estimates Using Data from the U.S. Climate Reference Network

Reliable procedures that accurately map surface insolation over large domains at high spatial and temporal resolution are a great benefit for making the predictions of potential and actual evapotranspiration that are required by a variety of hydrological and agricultural applications. Here, estimates of hourly and daily integrated insolation at 20-km resolution, based on Geostationary Operational Environmental Satellite (GOES) visible imagery are compared to pyranometer measurements made at 11 sites in the U.S. Climate Reference Network (USCRN) over a continuous 15-month period. Such a comprehensive survey is necessary in order to examine the accuracy of the satellite insolation estimates over a diverse range of seasons and land surface types. The relatively simple physical model of insolation that is tested here yields good results, with seasonally averaged model errors of 62 (19%) and 15 (10% )Wm 2 for hourly and daily-averaged insolation, respectively, including both clear- and cloudy-sky conditions. This level of accuracy is comparable, or superior, to results that have been obtained with more complex models of atmospheric radiative transfer. Model performance can be improved in the future by addressing a small elevation-related bias in the physical model, which is likely the result of inaccurate model precipitable water inputs or cloud-height assessments.

Effects of precipitation and cloud ice on brightness temperatures in AMSU moisture channels

Extinction by ice and rain at the AMSU frequencies used in water vapor profile retrievals is investigated with DMSP observations and brightness temperature simulations of a convective storm system. The simulations are based on mesoscale forecast model output of atmospheric, cloud, and rain profiles from which the absorption and scattering due to both liquid and frozen hydrometeors are calculated. Comparison with satellite observations indicates discrepancies of more than 90% (up to 60 K), of which only about 20% results from ignoring scattering by model-prescribed ice. The major source of error is the inability of the forecast model to produce the spatially localized high ice concentrations which cause the low microwave brightness temperatures. A criterion based on the difference between measured brightness temperatures at 183.31/spl plusmn/3 and 183.31/spl plusmn/1 GHz is suggested to screen out convective events before water vapor retrieval. Application to the case study examined improved agreement between simulated and observed brightness temperatures by up to a factor of two.

A note on first estimates of surface insolation from GOES-8 visible satellite data

Abstract Visible imagery from geostationary satellites have a long history of providing accurate estimates of surface insolation over large spatial domains and at high horizontal resolution. In 1995, the United States launched its second generation of these geostationary (GOES) satellites, GOES-8 and GOES-9, with somewhat different visible sensor characteristics than their predecessors (GOES 1–7). In this work, we discuss first results of the estimation of daily insolation from these new data and compare the results to a pyranometer network maintained in Wisconsin by the University of Wisconsin-Madison. These results appear to be good and will be applied to estimating potential evapotranspiration for areas in Wisconsin where such knowledge of surface insolation is of primary importance for the scheduling of irrigation.