Manfred Owe

Multisensor historical climatology of satellite‐derived global land surface moisture

global product and is consistent in its retrieval approach for the entire period of data record. The moisture retrievals are made with a radiative transfer-based land parameter retrieval model. The various sensors have different technical specifications, including primary wavelength, spatial resolution, and temporal frequency of coverage. These sensor specifications and their effect on the data retrievals are discussed. The model is described in detail, and the quality of the data with respect to the different sensors is discussed as well. Examples of the different sensor retrievals illustrating global patterns are presented. Additional validation studies were performed with large-scale observational soil moisture data sets and are also presented. The data will be made available for use by the general science community.

A methodology for surface soil moisture and vegetation optical depth retrieval using the microwave polarization difference index

A methodology for retrieving surface soil moisture and vegetation optical depth from satellite microwave radiometer data is presented. The procedure is tested with historical 6.6 GHz H and V polarized brightness temperature observations from the scanning multichannel microwave radiometer (SMMR) over several test sites in Illinois. Results using only nighttime data are presented at this time due to the greater stability of nighttime surface temperature estimation. The methodology uses a radiative transfer model to solve for surface soil moisture and vegetation optical depth simultaneously using a nonlinear iterative optimization procedure. It assumes known constant values for the scattering albedo and roughness, and that vegetation optical depth for H-polarization is the same as for V-polarization. Surface temperature is derived by a procedure using high frequency V-polarized brightness temperatures. The methodology does not require any field observations of soil moisture or canopy biophysical properties for calibration purposes and may be applied to other wavelengths. Results compare well with field observations of soil moisture and satellite-derived vegetation index data from optical sensors.

On the relationship between thermal emissivity and the normalized difference vegetation index for natural surfaces

Abstract The spatial variation of both the thermal emissivity (8–14/mu;m) and Normalized Difference Vegetation Index (NDVI) was measured for a series of natural surfaces within a savanna environment in Botswana. The measurements were performed with an emissivity-box and with a combined red and near-infrared radiometer, with spectral bands corresponding to NOAA/AVHRR. It was found that thermal emissivity was highly correlated with NDVI after logarithmic transformation, with a correlation coefficient of R = 0·94. This empirical relationship is of potential use for energy balance studies using thermal infrared remote sensing. The relationship was used in combination with AVHRR (GAC), AVHRR (LAC), and Landsat (TM) data to demonstrate and compare the spatial variability of various spatial scales.

BARE SOIL SURFACE RESISTANCE TO EVAPORATION BY VAPOR DIFFUSION UNDER SEMIARID CONDITIONS

Based on Kohsieks fast air circulation chamber, a method has been developed to measure the surface resistance to vapor diffusion in a drying topsoil. This resistance is important to estimate evaporation from bare soils using an aerodynamic resistance formulation. Measurements were done for a fine sandy loam during a dry down after artificial wetting. Surface resistance started to increase at a moisture content of 15% by volume in the 1-cm top layer, which is 50% of its moisture content at field capacity. Calculations of the aerodynamic resistance were corrected for stability and were used to isolate the real surface resistance from the bulk resistance. Resistances could be modeled as a function of the top 1 cm soil moisture and varied between approximately 10 s/m for a wet and several thousand seconds per meter for a dry top layer. The measurements demonstrated a very pronounced diurnal course due to drying of the very top layer during the day and recovery of the moisture profile during nighttime hours.

Land Surface Temperature from Ka-band (37 GHZ) Passive Microwave Observations

[1] An alternative to thermal infrared satellite sensors for measuring land surface temperature (Ts) is presented. The 37 GHz vertical polarized brightness temperature is used to derive Ts because it is considered the most appropriate microwave frequency for temperature retrieval. This channel balances a reduced sensitivity to soil surface characteristics with a relatively high atmospheric transmissivity. It is shown that with a simple linear relationship, accurate values for Ts can be obtained from this frequency, with a theoretical bias of within 1 K for 70% of vegetated land areas of the globe. Barren, sparsely vegetated, and open shrublands cannot be accurately described with this single channel approach because variable surface conditions become important. The precision of the retrieved land surface temperature is expected to be better than 2.5 K for forests and 3.5 K for low vegetation. This method can be used to complement existing infrared derived temperature products, especially during clouded conditions. With several microwave radiometers currently in orbit, this method can be used to observe the diurnal temperature cycles with surprising accuracy.

Analytical derivation of the vegetation optical depth from the microwave polarization difference index

A numerical solution for the canopy optical depth in an existing microwave-based land surface parameter retrieval model is presented. The optical depth is derived from the microwave polarization difference index and the dielectric constant of the soil. The original procedure used an approximation in the form of a logarithmic decay function to define this relationship and was derived through a series of lengthy polynomials. These polynomials had to be recalculated when the scattering albedo or antenna incidence angle changes. The new procedure is computationally more efficient and accurate.

Satellite remote sensing of soil moisture in Illinois, United States

To examine the utility of using satellite passive microwave observations to measure soil moisture over large regions, we conducted a pilot study using the scanning multichannel microwave radiometer (SMMR) on Nimbus-7, which operated from 1978 to 1987, and actual in situ soil moisture observations from the state of Illinois, United States, which began in 1981. We examined SMMR midnight microwave brightness temperatures on a 0.5° × 0.5° grid, and compared them with direct soil moisture measurements at 14 sites in Illinois for the period 1982–1987. The results suggest that both the polarization difference and the microwave emissivity for horizontal polarization at frequencies ≤18 GHz have real utility for use as a soil moisture information source in regions with grass or crops where the vegetation is not too dense. While SMMR observations ended in 1987, special sensor microwave/imager observations at 19 GHz start then and extend to the present, and advanced microwave scanning radiometer instruments will fly on satellites beginning soon. Together with SMMR, they have the potential to produce a soil moisture record over large regions for more than two decades and extend it into the future. Satellite observations from these low-resolution satellite instruments measure the component of large-scale long-term soil moisture variability that is related to atmospheric forcing (from precipitation, evapotranspiration, and snowmelt).

Further validation of a new methodology for surface moisture and vegetation optical depth retrieval

A series of validation studies for a recently developed soil moisture and optical depth retrieval algorithm is presented. The approach is largely theoretical, and uses a non-linear iterative optimization procedure to solve a simple radiative transfer equation for the two parameters from dual polarization satellite microwave brightness temperatures. The satellite retrievals were derived from night-time 6.6 GHz Nimbus Scanning Multichannel Microwave Radiometer (SMMR) observations, and were compared to soil moisture data sets from the USA, Mongolia, Turkmenistan and Russia. The surface temperature, which is also an unknown parameter in the model, is derived off-line from 37 GHz vertical polarized brightness temperatures. The new theoretical approach is independent of field observations of soil moisture or canopy biophysical measurements and can be used at any wavelength in the microwave region. The soil moisture retrievals compared well with the surface moisture observations from the various locations. The vegetation optical depth also compared well to time series of Normalized Difference Vegetation Index (NDVI) and showed similar seasonal patterns. From a global perspective, the satellite-derived surface soil moisture was consistent with expected spatial patterns, identifying both known dry areas such as deserts and semi-arid areas and moist agricultural areas very well. Spatial patterns of vegetation optical depth were found to be in agreement with NDVI. The methodology described in this study should be directly transferable to the Advanced Microwave Scanning Radiometer (AMSR) on the recently launched AQUA satellite.

Surface moisture and satellite microwave observations in semiarid southern Africa

Nimbus 7 scanning multichannel microwave radiometer 6.6-GHz passive microwave data were studied in relation to large-scale soil moisture estimates over a 3-year period in southeastern Botswana. An extensive data base of weekly surface soil moisture measurements was used with meteorological data to estimate pixel average soil moisture on a daily basis. The influence of the vegetation canopy on the surface emissivity was studied by partitioning the data set into classes on the basis of the normalized difference vegetation index. After correcting for the vegetation optical depth, a correlation of r = 0.84 was established between the normalized brightness temperature observations and surface soil moisture for the 3-year period.

On the Relationship between Thermodynamic Surface Temperatures and High Frequency (37 GHz) Vertical Polarization Brightness Temperatures under Semi-arid Conditions.

A method to estimate surface temperature from high-frequency microwave observations is presented. Microwave brightness temperature is a function of the emissivity and the physical temperature of the emitting layer, and therefore possesses a strong physical basis for the estimation of surface temperature. Field observations have shown that maximum and minimum daily air temperatures are strongly related to daytime (1200h) and night-time (2400h) surface temperature. Field measurements of surface temperature are also compared to METEOSAT thermal observations. Long-term daily maximum and minimum air temperatures are then used to derive datasets of daytime and night-time surface temperatures. The results indicate that 37 GHz vertical polarization brightness temperature provides a reasonable estimate of spatially averaged surface temperature. This approach could provide a useful tool for climate modelling, land surface processes investigations, and other energy balance applications by providing consistent and independent long-term estimates of daily global surface temperature.