Karen S. Humes

Mesoscale Monitoring of Soil Moisture across a Statewide Network

Soil moisture is an important component in many hydrologic and land–atmosphere interactions. Understanding the spatial and temporal nature of soil moisture on the mesoscale is vital to determine the influence that land surface processes have on the atmosphere. Recognizing the need for improved in situ soil moisture measurements, the Oklahoma Mesonet, an automated network of 116 remote meteorological stations across Oklahoma, installed Campbell Scientific 229-L devices to measure soil moisture conditions. Herein, background information on the soil moisture measurements, the technical design of the soil moisture network embedded within the Oklahoma Mesonet, and the quality assurance (QA) techniques applied to the observations are provided. This project also demonstrated the importance of operational QA regarding the data collected, whereby the percentage of observations that passed the QA procedures increased significantly once daily QA was applied.

An interdisciplinary field study of the energy and water fluxes in the atmosphere−biosphere system over semiarid rangelands : description and some preliminary results

Abstract Arid and semiarid rangelands comprise a significant portion of the earths land surface. Yet little is known about the effects of temporal and spatial changes in surface soil moisture on the hydrologic cycle, energy balance, and the feedbacks to the atmosphere via thermal forcing over such environments. Understanding this interrelationship is crucial for evaluating the role of the hydrologic cycle in surface-atmosphere interactions. This study focuses on the utility of remote sensing to provide measurements of surface soil moisture, surface albedo, vegetation biomass, and temperature at different spatial and temporal scales. Remote-sensing measurements may provide the only practical means of estimating some of the more important factors controlling land surface processes over large areas. Consequently, the use of remotely sensed information in biophysical and geophysical models greatly enhances their ability to compute fluxes at catchment and regional scales on a routine basis. However, model cal...

Single- and Dual-Source Modeling of Surface Energy Fluxes with Radiometric Surface Temperature

Abstract Single- and dual-source models of the surface energy transfer across the soil-vegetation-atmosphere interface were used in conjunction with remotely sensed surface temperature for computing the surface energy balance over heterogeneous surfaces. Both models are relatively simple so that only a few parameters are specified, making them potentially useful for computing surface fluxes with operational satellite observations. The models were tested with datasets collected from a semiarid rangeland environment with canopy cover generally less than 50% and a subhumid tallgrass prairie environment having canopy cover typically greater than 50%. For the semiarid site, differences between the single-source and dual-source model estimates of the sensible heat flux (H) and the observations averaged about 25%. For the tallgrass prairie, the disagreement between observations and single-source model estimates of H was significantly larger, averaging nearly 55%. The average difference between observations and t...

The scaling characteristics of remotely-sensed variables for sparsely-vegetated heterogeneous landscapes

With increasing interest in airborne and satellite-based sensors for mapping regional and global energy balance, there is a need to determine the uncertainty involved in aggregating remotely-sensed variables [surface temperature (Tk) and reflectance (π)] and surface energy fluxes [sensible (H) and latent (λE) heat flux] over large areas. This uncertainty is directly related to two factors: (1) the nonlinearity of the relation between the sensor signal and Tk, π, H orλE; and (2) the heterogeneity of the site. In this study, we compiled several remotely-sensed data sets acquired at different locations within a semi-arid rangeland in Arizona, at a variety of spatial and temporal resolutions. These data sets provided the range of data heterogeneities necessary for an extensive analysis of data aggregation. The general technique to evaluate uncertainty was to compare remotely-sensed variables and energy balance components calculated in two ways: first, calculated at the pixel resolution and averaged to the coarser resolution; and second, calculated directly at the coarse resolution by aggregating the fine-resolution data to the coarse scale. Results showed that the error in the aggregation of Tk and π was negligible for a wide range of conditions. However, the error in aggregation of H and λE was highly influenced by the heterogeneity of the site. Errors in H larger than 50% were possible under certain conditions. The conditions associated with the largest aggregation errors in H were: • sites which are composed of a mix of stable and unstable conditions; • sites which have considerable variations in aerodynamic roughness, especially for highly unstable conditions where the difference between surface and air temperature is large; and • sites which are characterized by patch vegetation, where the pixel resolution is less than or nearly-equal to the diameter of the vegetation ‘element’ (in most cases, the diameter of the dominant vegetation type or vegetation patch). Thus, knowledge of the surface heterogeneity is essential for minimizing error in aggregation of H and λE. Two schemes are presented for quantifying surface heterogeneity as a first step in data aggregation. These results emphasized the need for caution in aggregation of energy balance components over heterogeneous landscapes with sparse or mixed vegetation types.

Relationships between evaprorative fraction and remotely sensed vegetation index and microwave brightness temperature for semiarid rangelands

Abstract Measurements of the microwave brightness temperature (TB) with the Pushbroom Microwave Radiometer (PBMR) over the Walnut Gulch Experimental Watershed were made on selected days during the MONSOON 90 field campaign. The PBMR is an L-band instrument (21-cm wavelength) that can provide estimates of near-surface soil moisture over a variety of surfaces. Aircraft observations in the visible and near-infrared wavelengths collected on selected days also were used to compute a vegetation index. Continuous micrometeorological measurements and daily soil moisture samples were obtained at eight locations during the experimental period. Two sites were instrumented with time domain reflectometry probes to monitor the soil moisture profile. The fraction of available energy used for evapotranspiration was computed by taking the ratio of latent heat flux (LE) to the sum of net radiation (Rn) and soil heat flux (G). This ratio is commonly called the evaporative fraction (EF) and normally varies between 0 and 1 un...

Estimation of Surface Heat Fluxes at Field Scale Using Surface Layer Versus Mixed-Layer Atmospheric Variables with Radiometric Temperature Observations

Radiometric surface temperature observations TR(f), near-surface meteorological/surface energy flux (METFLUX), and atmospheric boundary layer (ABL) data were collected during the Washita ’94 Experiment conducted in the Little Washita Experimental Watershed near Chickasha, Oklahoma. The TR(f) measurements were made from ground and aircraft platforms near the METFLUX stations located over vegetated surfaces of varying amounts of cover and over bare soil. Continuous, half-hourly averaged ground-based TR(f) measurements essentially at the point scale were calibrated with periodic ground transect and aircraft-based TR(f) observations at coarser resolutions so that the continuous TR(f) measurements would be representative of surface temperatures at the field scale (i.e., on the order of 104 m2). The METFLUX data were collected nominally at 2 m above the surface, while ABL measurements were made in the lower 8‐10 km of the atmosphere. The ‘‘local’’ wind speed, u, and air temperature, TA, from the METFLUX stations, as well as the mixed-layer wind speed, UM, and potential temperature, QM, were used in a two-source energy balance model for computing fluxes with continuous TR(f) measurements from the various surfaces. Standard Monin‐ Obukhov surface layer similarity was used with the ‘‘local’’ u and TA data from the METFLUX stations. Bulk similarity approaches were used with the UM and QM data referenced either to ABL height or the top of the surface layer. This latter approach of using mixed-layer data to drive model computations for the different sites is similar to the so-called flux-aggregation schemes or methods proposed to account for subgrid variability in atmospheric models, such as the ‘‘tile’’ or ‘‘mosaic’’ approach. There was less agreement between modeled and measured fluxes when using mixedlayer versus local meteorological variables data for driving the model, and the type of bulk formulation used (i.e., whether local or regional surface roughness was used) also had a significant impact on the results. Differences between the flux observations and model predictions using surface layer similarity with local u and TA data were about 25% on average, while using the bulk formulations with UM and QM differences averaged about 30%. This larger difference was caused by an increase in biases and scatter between modeled and measured fluxes for some sites. Therefore, computing spatially distributed local-scale fluxes with ABL observations of mixed-layer properties will probably yield less reliable flux predictions than using local meteorological data, if available. Given the uncertainty in flux observations is about 20%, these estimates are still considered reasonable and moreover permit the mapping of spatially distributed surface fluxes at regional scales using a single observation of UM and QM with high resolution TR(f) data. Such TR(f) observations with a 90-m pixel resolution will be available from the Advanced Spaceborne Thermal Emission and Reflection Radiometer to be launched on NASA’s Earth Observing System.

Monitoring land surface fluxes using ASTER observations

This paper presents a review of methods for using remotely sensed data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) to estimate the energy fluxes from the land surface. The basic concepts of the energy balance at the land surface are presented along with an example of how remotely sensed surface brightness temperatures can be used to estimate the sensible heat. The example is from the Monsoon 1990 experiment conducted over an arid watershed in Arizona. In this case, surface temperatures derived from an aircraft thermal-infrared (TIR) sensor and vegetation and land use characteristics derived from a Landsat Thematic Mapper (TM) image were used in a two-source model to predict the surface heat fluxes. The agreement with ground measurements is reasonably good for the three days of observations.

An overview of the workshop on thermal remote sensing held at La Londe les Maures, France, September 20-24, 1993

Abstract This article reviews the major topics discussed at the Thermal Remote Sensing Workshop held at La Londe les Maures, France in 1993 and concludes with a list of new items and concepts suggested during the meeting

Spatially Distributed Sensible Heat Flux over a Semiarid Watershed. Part I: Use of Radiometric Surface Temperatures and a Spatially Uniform Resistance

Abstract Spatially distributed radiometric surface temperatures over a semiarid watershed were computed using remotely sensed data acquired with an aircraft-based multispectral scanner during the Monsoon ’90 Large Scale Field Experiment. The multispectral scanner data provide watershed coverage of surface temperature at a resolution of 6.3 m and nearly daily temporal resolution. At high spatial resolution, the surface temperature values appear to be correlated strongly with surface aspect; at more coarse spatial resolution, the surface temperatures variations across the watershed appear to be correlated with background soil moisture variations caused by highly localized precipitation events. The surface temperature data were aggregated to 400-m spatial resolution for the purpose of computing spatially distributed sensible heat fluxes over the watershed. The practicality of using a spatially uniform transfer coefficient was evaluated by examining the variability of surface and meteorological factors across...

Daytime net radiation estimated for a semiarid rangeland basin from remotely sensed data

The relationships between daytime averages of net radiation (Rn,dt) and solar radiation (Rs,dt) were investigated with data collected from the MONSOON 90 experiment conducted in a semiarid rangeland basin. Just as in many previous studies, a regression between Rn,dt and Rs,dt was performed. In an attempt to account for more of the variability in Rn,dt, soil moisture was included as an additional independent variable. The behavior of the ratio Rn,dt/Rs,dt was also investigated. It was found that both temporal and spatial variations in this ratio were mainly correlated with surface shortwave albedo and soil moisture. Measurements of microwave brightness temperatures from an L-band (21 cm wavelength) radiometer, sensitive to near-surface soil moisture, also showed a high correlation with Rn,dt/Rs,dt. Estimates of Rs,dt from the GOES-7 satellite were used with the soil moisture data to compute Rn,dt. The results indicate that improved estimates of basin-scale Rn,dt for semiarid rangelands can be obtained by including soil moisture measurements. This may lead to more accurate regional-scale estimates of daily ET with operational methods using satellite-based measurements. Comparisons between Rn,dt and Rs,dt during the dry and wet seasons suggested that the variation in surface albedo and temperature are required in order to fully account for observed differences in equations predicting Rn,dt and the ratio Rn,dt/Rs,dt.