Abstract

Observations of the surface radiometric temperature by the AVHRR sensor on board the NOAA-9 satellite during the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment conducted in central Kansas during 1987 are presented. The satellite observations were corrected for atmospheric effects using a path radiance model (MODTRAN3) and radiosonde measurements. Problems with this approach include the nonsimultaneity of the soundings with the overpass and errors involved in profile measurements. For the former, soundings before and after the overpass were interpolated to the time of the overpass. For the latter, some of the errors arise from the ±0.5°C uncertainty in the dry- and wet-bulb temperatures, which can produce up to a ±14% relative uncertainty in the water vapor. To overcome this uncertainty, the water vapor profiles were adjusted until the channel 4 and 5 temperature differences over a large reservoir were reduced to zero. This adjusted profile was then used over the entire site. The results are compared to ground broadband temperature readings at 10 sites and to aircraft results from the thermal channel of the NS001 sensor on the C-130 aircraft. The AVHRR values were found to be 5° to 6°C warmer than the average of the ground measurements. This difference is attributed to the fact that the ground measurements were made preferentially on well-vegetated surfaces while the AVHRR integrates over the entire site, which includes many warm surfaces.

Abstract

Roughness height for heat transfer is a crucial parameter in estimation of heat transfer between the land surface and the atmosphere. Although many empirical formulations have been proposed over the past few decades, the uncertainties associated with these formulations are shown to be large, especially over sparse canopies. In this contribution, a simple physically based model is derived for the estimation of the roughness height for heat transfer. This model is derived from a complex physical model based on the “localized near-field” Lagrangian theory. This model (called Massman's model) and another recently proposed model derived by fitting simulation results of a simple multisource bulk transfer model (termed Blümel's model) are evaluated using three experimental datasets. The results of the model performances are judged by using the derived roughness values to compute sensible heat fluxes with the bulk transfer formulation and comparing these computed fluxes to the observed sensible heat fluxes. It is concluded, on the basis of comparison of calculated versus observed sensible heat fluxes, that both the current model and Blümel's model provide reliable estimates of the roughness heights for heat transfer. The current model is further shown to be able to explain the diurnal variation in the roughness height for heat transfer. On the basis of a sensitivity analysis, it is suggested that, although demanding, most of the information needed for both models is amendable by satellite remote sensing such that their global incorporation into large-scale atmospheric models for both numerical weather prediction and climate research merits further investigation.

Abstract

The use of remotely sensed near-surface soil moisture for the estimation of evaporation is investigated. Two widely used parameterizations of evaporation, the so-called α and β methods, which use near-surface soil moisture to reduce some measure of potential evaporation, are studied. The near-surface soil moisture is provided by a set of L- and S-band microwave radiometers, which were mounted 13 m above the surface. It is shown that soil moisture measured with a passive microwave sensor in combination with the β method yields reliable estimates of evaporation, whereas the α method is not as robust.

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 under daytime convective conditions with minimal advection. A wide range of environmental conditions existed during the field campaign, resulting in average EF values for the study area varying from 0.4 to 0.8 and values of TB ranging from 220 to 280 K. Comparison between measured TB and EF for the eight locations showed an inverse relationship with a significant correlation (r ² = 0.69). Other days were included in the analysis by estimating TB with the soil moisture data. Because transpiration from the vegetation is more strongly coupled to root zone soil moisture, significant scatter in this relationship existed at high values of TB or dry near-surface soil moisture conditions. It caused a substantial reduction in the correlation with r ² = 0.40 or only 40% of the variation in EF being explained by TB. The variation in EF under dry near-surface soil moisture conditions was correlated to the amount of vegetation cover estimated with a remotely sensed vegetation index. These findings indicate that information obtained from optical and microwave data can be used for quantifying the energy balance of semiarid areas. The microwave data can indicate when soil evaporation is significantly contributing to EF, while the optical data is helpful for quantifying the spatial variation in EF due to the distribution of vegetation cover.

Arid and semiarid rangelands comprise a significant portion of the earth's 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 calculations for different climates and ecosystems need verification. This requires that the remotely sensed data and model computations be evaluated with ground-truth data collected at the same areal scales.

The present study (MONSOON 90) attempts to address this issue for semiarid rangelands. The experimental plan included remotely sensed data in the visible, near-infrared, thermal, and microwave wavelengths from ground and aircraft platforms and, when available, from satellites. Collected concurrently were ground measurements of soil moisture and temperature, energy and water fluxes, and profile data in the atmospheric boundary layer in a hydrologically instrumented semiarid rangeland watershed. Field experiments were conducted in 1990 during the dry and wet or “monsoon season” for the southwestern United States. A detailed description of the field campaigns, including measurements and some preliminary results are given.