Eni G. Njoku

The Soil Moisture Active Passive (SMAP) Mission

The Soil Moisture Active Passive (SMAP) mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Councils Decadal Survey. SMAP will make global measurements of the soil moisture present at the Earths land surface and will distinguish frozen from thawed land surfaces. Direct observations of soil moisture and freeze/thaw state from space will allow significantly improved estimates of water, energy, and carbon transfers between the land and the atmosphere. The accuracy of numerical models of the atmosphere used in weather prediction and climate projections are critically dependent on the correct characterization of these transfers. Soil moisture measurements are also directly applicable to flood assessment and drought monitoring. SMAP observations can help monitor these natural hazards, resulting in potentially great economic and social benefits. SMAP observations of soil moisture and freeze/thaw timing will also reduce a major uncertainty in quantifying the global carbon balance by helping to resolve an apparent missing carbon sink on land over the boreal latitudes. The SMAP mission concept will utilize L-band radar and radiometer instruments sharing a rotating 6-m mesh reflector antenna to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every two to three days. In addition, the SMAP project will use these observations with advanced modeling and data assimilation to provide deeper root-zone soil moisture and net ecosystem exchange of carbon. SMAP is scheduled for launch in the 2014-2015 time frame.

Soil moisture retrieval from AMSR-E

The Advanced Microwave Scanning Radiometer (AMSR-E) on the Earth Observing System (EOS) Aqua satellite was launched on May 4, 2002. The AMSR-E instrument provides a potentially improved soil moisture sensing capability over previous spaceborne radiometers such as the Scanning Multichannel Microwave Radiometer and Special Sensor Microwave/Imager due to its combination of low frequency and higher spatial resolution (approximately 60 km at 6.9 GHz). The AMSR-E soil moisture retrieval approach and its implementation are described in this paper. A postlaunch validation program is in progress that will provide evaluations of the retrieved soil moisture and enable improved hydrologic applications of the data. Key aspects of the validation program include assessments of the effects on retrieved soil moisture of variability in vegetation water content, surface temperature, and spatial heterogeneity. Examples of AMSR-E brightness temperature observations over land are shown from the first few months of instrument operation, indicating general features of global vegetation and soil moisture variability. The AMSR-E sensor calibration and extent of radio frequency interference are currently being assessed, to be followed by quantitative assessments of the soil moisture retrievals.

Passive microwave remote sensing of soil moisture

Abstract Microwave remote sensing provides a unique capability for direct observation of soil moisture. Remote measurements from space afford the possibility of obtaining frequent, global sampling of soil moisture over a large fraction of the Earths land surface. Microwave measurements have the benefit of being largely unaffected by cloud cover and variable surface solar illumination, but accurate soil moisture estimates are limited to regions that have either bare soil or low to moderate amounts of vegetation cover. A particular advantage of passive microwave sensors is that in the absence of significant vegetation cover soil moisture is the dominant effect on the received signal. The spatial resolutions of passive microwave soil moisture sensors currently considered for space operation are in the range 10–20 km. The most useful frequency range for soil moisture sensing is 1–5 GHz. System design considerations include optimum choice of frequencies, polarizations, and scanning configurations, based on trade-offs between requirements for high vegetation penetration capability, freedom from electromagnetic interference, manageable antenna size and complexity, and the requirement that a sufficient number of information channels be available to correct for perturbing geophysical effects. This paper outlines the basic principles of the passive microwave technique for soil moisture sensing, and reviews briefly the status of current retrieval methods. Particularly promising are methods for optimally assimilating passive microwave data into hydrologic models. Further studies are needed to investigate the effects on microwave observations of within-footprint spatial heterogeneity of vegetation cover and subsurface soil characteristics, and to assess the limitations imposed by heterogeneity on the retrievability of large-scale soil moisture information from remote observations.

Retrieval of land surface parameters using passive microwave measurements at 6-18 GHz

An approach is evaluated for retrieval of land surface parameters (soil moisture, vegetation water content, and surface temperature) using satellite microwave radiometer data in the 6-18 GHz frequency range. The approach is applicable to data that will be acquired by the Advanced Microwave Scanning Radiometer (AMSR), planned for launch on the Japanese Advanced Earth Observing Satellite (ADEOS)-II and Earth Observing System (EOS) PM-1 platforms in 1999 and 2000, respectively. The retrieval method is based on a radiative transfer (RT) model for land-surface and atmospheric emission, with model coefficients that can be tuned over specific calibration regions and applied globally. The method uses an iterative, least-squares algorithm, based on six channels of radiometric data. Simulations using this algorithm indicate that, for an assumed sensor noise of 0.3 K in all channels, soil moisture and vegetation water content retrieval accuracies of 0.06 g cm/sup -3/ and 0.15 kg m/sup -2/, respectively, should be achievable in regions of vegetation water content less than approximately 1.5 kg m/sup -2/. A surface temperature accuracy of 2 C should be achievable, except for bare soils, where discrimination between moisture and temperature variability is difficult using this algorithm. These accuracies are for retrievals averaged over the sensor footprint, and they exclude conditions of precipitation, open water, snow cover, frozen ground, or high topographic relief within the footprint. The algorithm has been tested using data from the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) for the years 1982-1985, over the African Sahel, and the retrieval results compared to output from an operational numerical weather prediction model.

Solving the inverse problem for soil moisture and temperature profiles by sequential assimilation of multifrequency remotely sensed observations

An algorithm is developed to solve the inverse problem for the retrieval of the soil moisture and temperature profiles based on remotely sensed observations of multispectral irradiance. A model of coherent wave radiative transfer and a model of coupled heat and moisture diffusion in porous media are combined in order to estimate the liquid volumetric water content and temperature profiles in a soil column using low-frequency passive microwave and infrared emitted radiation observations and without the use of empirical relations. The central purpose of this mainly theoretical paper is to pose the inverse problem and present the physics-based algorithm as the solution. The algorithm is tested on a basic synthetic example in order to ascertain that the retrieval is feasible. Additional work in the future is necessary and planned in order to test the algorithm with field observations, extend it to include vegetation, and refine it for detail in the specification of heterogeneity in soil types and boundary conditions. >

A semiempirical model for interpreting microwave emission from semiarid land surfaces as seen from space

A radiative transfer model for simulating microwave brightness temperatures over land surfaces is described. The model takes into account sensor viewing conditions (spacecraft altitude, viewing angle, frequency, polarization) and atmospheric parameters over a soil surface characterized by its moisture, roughness, and temperature and covered with a layer of vegetation characterized by its temperature, water content, single scattering albedo, structure and percent coverage. In order to reduce the influence of atmospheric and surface temperature effects, the brightness temperatures are expressed as polarization ratios that depend primarily on the soil moisture and roughness, canopy water content, and percentage of cover. The approach used is described, and the sensitivity of the polarization ratio to these parameters is investigated. Simulation of the temporal evolution of the microwave signal over semiarid areas in the African Sahel is presented and compared to actual satellite data from the SMMR instrument on Nimbus-7. >

Global survey and statistics of radio-frequency interference in AMSR-E land observations

Radio-frequency interference (RFI) is an increasingly serious problem for passive and active microwave sensing of the Earth. To satisfy their measurement objectives, many spaceborne passive sensors must operate in unprotected bands, and future sensors may also need to operate in unprotected bands. Data from these sensors are likely to be increasingly contaminated by RFI as the spectrum becomes more crowded. In a previous paper we reported on a preliminary investigation of RFI observed over the United States in the 6.9-GHz channels of the Advanced Microwave Scanning Radiometer (AMSR-E) on the Earth Observing System Aqua satellite. Here, we extend the analysis to an investigation of RFI in the 6.9- and 10.7-GHz AMSR-E channels over the global land domain and for a one-year observation period. The spatial and temporal characteristics of the RFI are examined by the use of spectral indices. The observed RFI at 6.9 GHz is most densely concentrated in the United States, Japan, and the Middle East, and is sparser in Europe, while at 10.7 GHz the RFI is concentrated mostly in England, Italy, and Japan. Classification of RFI using means and standard deviations of the spectral indices is effective in identifying strong RFI. In many cases, however, it is difficult, using these indices, to distinguish weak RFI from natural geophysical variability. Geophysical retrievals using RFI-filtered data may therefore contain residual errors due to weak RFI. More robust radiometer designs and continued efforts to protect spectrum allocations will be needed in future to ensure the viability of spaceborne passive microwave sensing.

The hydrosphere State (hydros) Satellite mission: an Earth system pathfinder for global mapping of soil moisture and land freeze/thaw

The Hydrosphere State Mission (Hydros) is a pathfinder mission in the National Aeronautics and Space Administration (NASA) Earth System Science Pathfinder Program (ESSP). The objective of the mission is to provide exploratory global measurements of the earths soil moisture at 10-km resolution with two- to three-days revisit and land-surface freeze/thaw conditions at 3-km resolution with one- to two-days revisit. The mission builds on the heritage of ground-based and airborne passive and active low-frequency microwave measurements that have demonstrated and validated the effectiveness of the measurements and associated algorithms for estimating the amount and phase (frozen or thawed) of surface soil moisture. The mission data will enable advances in weather and climate prediction and in mapping processes that link the water, energy, and carbon cycles. The Hydros instrument is a combined radar and radiometer system operating at 1.26 GHz (with VV, HH, and HV polarizations) and 1.41 GHz (with H, V, and U polarizations), respectively. The radar and the radiometer share the aperture of a 6-m antenna with a look-angle of 39/spl deg/ with respect to nadir. The lightweight deployable mesh antenna is rotated at 14.6 rpm to provide a constant look-angle scan across a swath width of 1000 km. The wide swath provides global coverage that meet the revisit requirements. The radiometer measurements allow retrieval of soil moisture in diverse (nonforested) landscapes with a resolution of 40 km. The radar measurements allow the retrieval of soil moisture at relatively high resolution (3 km). The mission includes combined radar/radiometer data products that will use the synergy of the two sensors to deliver enhanced-quality 10-km resolution soil moisture estimates. In this paper, the science requirements and their traceability to the instrument design are outlined. A review of the underlying measurement physics and key instrument performance parameters are also presented.

A preliminary survey of radio-frequency interference over the U.S. in Aqua AMSR-E data

A spectral difference method is used to quantify the magnitude and extent of radio-frequency interference (RFI) observed over the United States in the Aqua AMSR-E radiometer channels. A survey using data from the AMSR-E instrument launched in May 2002 shows the interference to be widespread in the C-band (6.9 GHz) channels. The RFI is located mostly, but not always, near large highly populated urban areas. The locations of interference are persistent in time, but the magnitudes show temporal and directional variability. Strong and moderate RFI can be identified relatively easily using an RFI index derived from the spectral difference between the 6.9- and 10.7-GHz channels. Weak RFI is difficult to distinguish, however, from natural geophysical variability. These findings have implications for future microwave sensing at C-band, particularly over land areas. An innovative concept for radiometer system design is also discussed as a possible mitigation approach.

Error sources and feasibility for microwave remote sensing of ocean surface salinity

A set of geophysical error sources for the microwave remote sensing of ocean surface salinity have been examined. The error sources include the sea surface temperature, sea surface roughness, atmospheric gases, ionospheric Faraday rotation, and solar and Galactic emission sources. It is shown that the brightness temperature effects of a few kelvin can be expected for most of these error sources. The key correction requirements for accurate salinity measurements are the knowledge accuracy of 0.5/spl deg/C for the sea surface temperature (SST), 10 mbar for the surface air pressure, 2/spl deg/C for the surface air temperature, 0.20 accuracy for the Faraday rotation, and surface roughness equivalent to 0.3 m s/sup -1/ for the surface wind speed. We suggest the use of several data products for corrections, including the AMSR-type instruments for SST and liquid cloud water, the AMSU-type product for air temperature, the scatterometer products or numerical weather analysis for the air pressure, coincidental radar observations with 0.2 dB precision for surface roughness, and on-board polarimetric radiometer channel for Faraday rotation. The most significant sky radiation is from the Sun. A careful design of the antenna is necessary to minimize the leakage of solar radiation or reflection into the antenna sidelobes. The narrow-band radiation from Galactic hydrogen clouds with a bandwidth of less than 1 MHz is also significant, but can be corrected with a radio sky survey or minimized with a notched (band-rejection) filter centered at 1.421 GHz. The other planetary and Galactic radio sources can also be flagged with a small data loss. We have performed a sampling analysis for a polar-orbiting satellite with 900 km swath width to determine the number of satellite observations over a given surface grid cell during an extended period. Under the assumption that the observations from different satellite passes are independent, it is suggested that an accuracy of 0.1 psu (practical salinity unit) is achievable for global monthly 10 latitude by 10 longitude gridded products.