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The social benefits to humans of a global knowledge of soil moisture and ocean salinity are numerous and varied.

Soil moisture variations affect the evolution of weather and climate over continental regions. Enhancement of numerical weather prediction models and seasonal climate models resulting in improved seasonal climate predictions will benefit climate-sensitive socioeconomic activities, including water management, agriculture, and fire, flood and drought hazards monitoring.

Soil moisture strongly affects plant growth and hence agricultural productivity, especially during conditions of water shortage, the most severe of which is drought. At present, there is no global in situ network for soil moisture. Global estimates of soil moisture, and in turn, plant water stress, must be derived from models.

These model predictions (and hence drought monitoring) could be greatly enhanced through assimilation of soil moisture observations.

Soil moisture also is a key variable in water related natural hazards, such as floods and landslides. High-resolution observations of soil moisture lead to improved flood forecasts, especially for intermediate-to-large watersheds where most flood damage occurs. The surface soil moisture state is key to partitioning of precipitation into infiltration and runoff. Hydrologic forecast systems initialized with mapped highresolution soil moisture fields will open a new era in operational flood forecasting. Furthermore, soil moisture in mountainous areas is one of the most important determinants of landslides.

Soil moisture data will provide information on water availability for plant productivity and potential yield. The availability of direct observations of soil moisture will allow significant improvements in operational crop productivity and crop waterstress information systems by providing realistic soil moisture observations for the models.

Improved seasonal soil moisture forecasts will directly improve famine early warning systems, particularly in sub-Saharan Africa and South Asia where hunger remains a major human health factor. Indirect benefits will also be realized as soil moisture data enables better weather forecasts which lead to improved predictions of heat stress and virus-spreading rates. Soil moisture data will also benefit the emerging field of landscape epidemiology (aimed at identifying and mapping vector habitats for human diseases such as malaria), where direct observations of soil moisture provide valuable information related to vector population dynamics.

Coincidently, human safety and prosperity depend on better ocean observing systems. Speedy diagnosis of the temper and vital signs of the oceans matters increasingly to the well being of humanity.

Current ocean observing systems suffer from major gaps in observational coverage which can be greatly improved by satellites which provide a high-altitude window on such marine characteristics as sea surface salinity and roughness, temperature, currents, ice cover and shifting meadow-like areas where marine plants grow. Scientists envisage an ongoing, integrated ocean observing system that routinely surveys and monitors conditions and offers prompt diagnoses and timely forecasts of problems - practical information of benefit to humanity in many ways.

Deeper understanding of ocean behaviour will help society better forecast and protect itself from catastrophic storms such as hurricanes, typhoons and tsunamis. Better ocean information will improve short- and long-range weather and climate prediction, thereby strengthening disaster preparedness and damage mitigation and strategies for agricultural and seafood harvests. As well, better ocean observing will improve safety of the marine transportation network - which conveys 90% of goods traded internationally - with accurate, timely information about ocean conditions.

Among the benefits offered by better ocean observing: measurement of sea surface temperatures and circulation could predict movement of fish from traditional waters, and even outbreaks of disease, which have been associated with warmer water, while monitoring pollution will help predict toxic algal blooms.

Oceans are a growing source of energy - oil and especially natural gas - as operators reach into the seafloor in deeper and deeper parts of the ocean with multibillion dollar facilities. Offshore wind farms would also depend on timely, reliable information on ocean conditions. Better ocean observation will help harness various energy sources safely and efficiently with minimal environmental impact.

A more fully developed ocean observing system will foster important new insights into how altered ocean conditions, including warmer water, circulation and increasing acidity, affect weather, climate and the role of the oceans as a carbon sink. Scientists want to know how warmer water, for example, impacts microscopic life forms that consume some 50 giga-tonnes of carbon per year, about the same as all plants and trees on land.

As the planet's primary reservoir, oceans govern the global water cycle. Improved ocean observations will help scientists better understand precipitation patterns.

A majority of life on Earth eats, swims, crawls, and lives in oceans. Water temperatures and circulation affect where species live and travel, as well as the distribution of nutrients, plankton and on up the food chain. A global ocean observing system such as SMOS will illuminate the impact of shifting ocean conditions and pollution on marine and coastal ecosystems and the distribution, abundance and biodiversity of organisms.

In summary, the SMOS objectives are to demonstrate the use of L-Band 2-D interferometric radiometry from space

• To monitor on a global scale soil moisture over land surfaces,

• To monitor on a global scale salinity over oceans, and

• To improve the characterisation of ice and snow covered surfaces for

• Advancing climatological, oceanographic, meteorological, hydrological, agronomical and glaciological science,

• Assessing the potential of such measurements to contribute to improve the management of water resources.

Regarding the technological evolution of the MIRAS design for SMOS, the concept of aperture synthesis was advanced in the field of radio astronomy as a means of achieving the finest resolving power with an antenna array that uses a relatively small number of individual elements. The objective of this technique is to achieve the best resolution at minimum cost. A prime example is the Very Large Array (VLA) shown in Fig. 2 that uses a "Y' configuration of elements to achieve the resolution of a filled array whose diameter is equal to that of the circle that encloses the "Y" (Napier et al. 1983). Because of phase fidelity offered by microwave components, antenna complexity can be replaced by signal processing complexity to obtain resolutions which could otherwise not be achieved. Indeed, radio telescopes utilizing aperture synthesis and very long baseline interferometry rival and even exceed the resolution achieved by some of the best earth-based optical telescopes (Swift etal. 1991).

Fig. 2 Very Large Array (VLA) at the National Radio Astronomy Observatory (NRAO) (Napier et al. 1983)

Space-based microwave applications in earth science are a much younger discipline than radio astronomy. As more geophysical-product users become accustomed to passive microwave satellite data, a demand is developing for both better spatial resolution and for the addition of frequencies as low as 1.4 GHz. These demands now place the space technologist in a similar quandary to radio astronomers 50 years ago; large, mechanically scanned filled apertures are just too costly to place into orbit. The ground rules for earth observation are somewhat different to those for radio astronomy. The spacecraft orbits at 6.5 km/s, so that processing must be done more rapidly. The earth is an extended source, whereas astronomical sources are embedded in a cold cosmic background which influences signal-to-noise ratios and sampling requirements.

Interferometric aperture synthesis was first proposed in the 1980's as an alternative to real-aperture radiometry for earth observation from space at low microwave frequencies with high spatial resolution (Ruf et al. 1988). An L-Band radiometer using real aperture for across track and interferometric aperture synthesis for along-track is described in (Le Vine et al. 2001). A radiometer using aperture synthesis in both directions (MIRAS) was proposed in (Martin-Neira and Goutoule 1997). In the meantime, extensive work has been done to improve the understanding of such a radiometer (Camps 1996).

The interferometer shown in Fig. 3 is the basic building block of the aperture synthesis technique developed for earth observation (Swift et al. 1991). If the outputs

of the two isotropic antenna elements are multiplied together, it can be shown (see (Kraus 1966), for example) that the equivalent measurement is described by the following formula:

where X is the electromagnetic wavelength, 0 is the incidence angle and d is the spacing between elements. V is known as the "visibility" function in line with the term commonly used in radio astronomy. If the visibility function is sequentially measured for 0 < d < D, then V can be defined as the Fourier transform of the thermal emission, or brightness temperature, of the scene. The scene can then be reconstructed by performing the Fourier inverse. The resolution of the measurement is determined by the total baseline D, and not the dimension of the antenna elements. Furthermore, only discrete samples with d equal to integer half wavelengths are required for perfect reconstruction of the scene with spatial resolution determined by D.

Unfortunately, such a scheme is not practical from low earth orbit because the forward motion of the spacecraft limits the time on target and hence sensitivity. A practical system requires simultaneous sampling of all integer half wavelengths distributed over the baseline. This dilemma has led to the concept of thinned array radiometry (Moffett 1968). The objective is to appropriately distribute a small number of elements over a baseline, perform power divisions of each output, and then perform the cross-correlations to generate the complete set of visibility functions. An example is shown in Fig. 4. In this example, five elements perform the work of eight. Although the savings are trivial in this case, thinning geometrically increases as the size of the array increases. This is a desirable characteristic since antennas become more expensive as the electrical size increases (Swift et al. 1991).

The thinned array concept offers interesting cost benefit trade-offs. One tradeoff is the exchange of antenna complexity for system complexity. In the example cited, five receivers and fifteen correlations are utilized to image the scene. This particular trade-off option of thinned arrays has become attractive as a result of advances that have occurred in microwave and computer technology. However it should be noted that the system complexity is considerable as the array thinning becomes more significant.

The other trade-off relates to signal-to-noise considerations. The figure of merit of a single total power radiometer is determined by AT, the measurement standard deviation, as given by the following formula:

where Tsys is the system noise temperature, B is the system bandwidth, and t is the post-detection integration time. Because of the type of processing used in aperture

At =Is2L

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