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A microwave imaging sensor, built for flight on the Defense Meteorological Satellite Program spacecraft, is discussed. Major elements of the sensor development program are summarized as background for planning a data archival program useful for climate research.
Global fields of precipitable water W from the special sensor microwave imager were compared with those from the European Center for Medium Range Weather Forecasts (ECMWF) model. They agree over most ocean areas; both data sets capture the two annual cycles examined and the interannual anomalies during an ENSO episode. They show significant differences in the dry air masses over the eastern tropical-subtropical oceans, particularly in the Southern Hemisphere. In these regions, comparisons with radiosonde data indicate that overestimation by the ECMWF model accounts for a large part of the differences. As a check on the W differences, surface-level specific humidity Q derived from W, using a statistical relation, was compared with Q from the ECMWF model. The differences in Q were found to be consistent with the differences in W, indirectly validating the Q-W relation. In both W and Q, SSMI was able to discern clearly the equatorial extension of the tongues of dry air in the eastern tropical ocean, while both ECMWF and climatological fields have reduced spatial gradients and weaker intensity.
A unified set of algorithms for the estimation of atmospheric parameters over the ocean is assembled, making it possible to apply data from the Special Sensor Microwave Imager (SSM/I) to case studies of weather systems over the ocean. The problems of sensor resolution and cross-parameter contamination are examined. The usefulness of the algorithms for obtaining the surface-wind-speed fields, integrated water vapor, cloud liquid water, and precipitation from SSM/I brightness temperature data over the ocean is demonstrated.
The final acts of the 1979 World Administrative Radio Conference (WARC) were analyzed to determine potential interference to remote passive microwave sensors. Using interferer populations determined from the U.S. Government and FCC Master File Lists and assuming uniform geographical distribution of interferers, the level of interference from shared services and active services in adjacent and subharmonic bands was calculated for each of the 22 passive sensing bands. In addition, due to the theoretically large antennas required for passive sensing, an analysis was performed to determine if smaller antennas, i.e., relaxed resolution requirements, would have an effect on interference and to what extent.
We present an overview of the 2024 West-Coast Hyperspectral Microwave Sensor Intensive Experiment(WHyMSIE). WHyMSIE is a joint NASA-NOAA multi-sensor airborne experiment, embracing passive and active sensors from the Program of Record (PoR) along with novel technology funded through the NASA ESTO Instrument Incubation Program. At the core of this effort is the demonstration of the Conical Scanning Millimeter-wave Imaging Radiometer Hyperspectral (CoSMIR-H) instrument, a PBL DSI funded effort to develop hyperspectral sounding capability in the thermal microwave domain finalized to improved temperature and water vapor soundings in the Earth’s Planetary Boundary Layer (PBL). An overview of the field campaign design, instrument payload and validation plan is presented here.
A series of 10 aircraft flights was conducted over agricultural fields to evaluate relationships between observed surface soil moisture and soil moisture predicted using passive microwave sensor observations. An a priori approach was used to predict values of surface soil moisture for three types of fields: tilled corn, no-till corn with soybean stubble, and idle fields with corn stubble. Acceptable predictions were obtained for the tilled corn fields, while poor results were obtained for the others. The source of error is suspected to be the density and orientation of the surface stubble layer; however, further research is needed to verify this explanation. Temporal comparisons between observed, microwave predicted, and soil water-simulated moisture values showed similar patterns for tilled well-drained fields. Divergences between the observed and simulated measurements were apparent on poorly drained fields. This result may be of value in locating and mapping hydrologic contributing areas.
Attention is given to the prime objective of the NASA validation program, namely, to establish quantitative relationships between the sea ice parameters derived from the special sensor microwave imager (SSM/I) using an algorithm originally developed for the Nimbus 7 SMMR. The underlying philosophy of the validation program is that confidence in the SSM/I algorithm products is achieved not so much by detailed comparison with localized surface observations as by consistency with independent spatially and temporally coincident data sets. The results of the satellite and aircraft comparisons that serve as the basis for the validation of the NASA SSMI/I sea ice algorithm are presented. High-resolution radiometer and C-band SAR imagery from the March 1988 NASA and Navy SSM/I underflights are used to verify the location of the ice edge and to validate the sea ice concentrations as determined by the SSM/I algorithm. These studies are argued to provide the most comprehensive measure to date of the accuracy of sea ice products derived from a spaceborne multichannel microwave imager.
The method proposed by Liu (1984) is used to estimate monthly averaged evaporation over the global oceans from 1 yr of special sensor microwave imager (SDSM/I) data. Intercomparisons involving SSM/I and in situ data are made over a wide range of oceanic conditions during August 1987 and February 1988 to determine the source of errors in the evaporation estimates. The most significant spatially coherent evaporation errors are found to come from estimates of near-surface specific humidity, q. Systematic discrepancies of over 2 g/kg are found in the tropics, as well as in the middle and high latitudes. The q errors are partitioned into contributions from the parameterization of q in terms of the columnar water vapor, i.e., the Liu q/W relationship, and from the retrieval algorithm for W. The effects of W retrieval errors are found to be smaller over most of the global oceans and due primarily to the implicitly assumed vertical structures of temperature and specific humidity on which the physically based SSM/I retrievals of W are based.
A microwave technique has been developed for detecting ice build-up on the wing surfaces of commercial airliners and highway bridges. A microstrip patch antenna serves as the sensor, with changes in the resonant frequency and impedance being dependent upon the overlying layers of ice, water and glycol mixtures. The antenna sensor is conformably mounted on the wing. The depth and dielectric constants of the layers are measured by comparing the complex resonant admittance with a calibrated standard. An initial breadboard unit has been built and tested. Additional development is now underway. Another commercial application is in the robotics field of remote sensing of coal seam thickness.
A microwave technique has been developed for detecting ice build-up on the wing surfaces of commercial airliners and highway bridges. A microstrip patch antenna serves as the sensor, with changes in the resonant frequency and impedance being dependent upon the overlying layers of ice, water, and glycol mixtures. The antenna sensor is conformably mounted on the wing. The depth and dielectric constants of the layers are measured by comparing the complex resonant admittance with a calibrated standard. An initial breadboard unit has been built and tested. Additional development is now underway.
The present study describes the validation of the the NASA team algorithm for the determination of sea ice concentrations from the Defense Meteorological Satellite Program special sensor microwave imager (SSM/I). A total of 28 cloud-free Landsat scenes were selected to permit validation of the passive microwave ice concentration algorithm for a range of ice concentrations and ice types. The sensitivity of the NASA team algorithm to the selection of locally and seasonally adjusted algorithm parameters is discussed. Mean absolute differences between SSM/I and Landsat ice concentrations are within 1 percent during fall using local and global tie points (standard deviations of the difference are +/-3.1 and +/-6.2 percent, respectively). In areas with greater amounts of nilas and young ice, the NASA team algorithm was found to underestimate ice concentrations by as much as 9 percent. It is inferred that the standard deviation between SSM/I and Landsat ice concentrations decreases from +/-7 to +/-5 percent with local tie points compared to the global ones for spring and fall.
Since July 1987, the Remote Sensing Systems (Santa Rosa, California) routinely computes from first principles the wind speed from Special Sensor Microwave Imager (SSM/I) measurements of the intensity of microwave radiation emitted at the ocean surface. The accuracy of monthly-mean SSM/I wind speeds is determined by comparisons with moored-buoy wind measurements, which were recorded by four different institutions at 44 sites in the Atlantic and Pacific Oceans during July 1987 to December 1989. All results for 1988 were virtually identical with 1989. The range of monthly mean moored-buoy wind speeds was 2-10 m/s. The rms difference of 697 monthly-mean matchups of the composite 1988 and 1989 data set was 1.2 m/s. The rms differences were smaller in the equatorial zone and higher in middle latitudes, in accord with the monthly standard deviation. At middle latitudes, the time series of rms differences displayed an annual cycle. In the equatorial zone, the agreement between SSM/I and in situ data was better in regions with a lesser amount of clouds, and vice versa. For SSM/I monthly standard deviations of 1-2, 2-3, and 3-4 m/s, the average absolute values of the monthly-mean difference between SSM/I and moored-buoy wind speeds were 0.6, 0.9, and 1.4 m/s, respectively.
Since July 1987 the Remote Sensing Systems, Santa Rosa, California, routinely computes from first principles the wind speed from Special Sensor Microwave Imager (SSM/I) measurements of the intensity of microwave radiation emitted at the ocean surface. The accuracy of monthly-mean SSM/I wind speeds is determined by comparisons with moored-buoy wind measurements, which were recorded by four different institutions at 44 sites in the Atlantic and Pacific Oceans during July 1987 to December 1989. All results for 1988 were virtually identical with 1989. The range of monthly mean moored-buoy wind speeds was 2-10 m s^(-1). During 1987, the equatorial matchups were not equivalent with 1998 and 1989, and the cause remains unknown. The root-mean-square (rms) difference of 697 monthly-mean matchups of the composite 1988 and 1989 data set was 1.2 m s^(-1). The rms differences were smaller in the equatorial zone and higher in middle latitudes, in accord with the monthly standard deviation. At middle latitudes the time series of rms differences displayed an annual cycle. In the equatorial zone the agreement between SSM/I and in situ data was better in regions with a lesser amount of clouds, and vice versa. For SSM/I monthly standard deviations of 1-2, 2-3, and 3-4 m s^(-1), the average absolute values of the monthly-mean difference between SSM/I and moored-buoy wind speeds were 0.6, 0.9, and 1.4 m s^(-1), respectively.
The relationship between surface properties and echo characteristics, as determined by radar technology, is discussed; echo enhancement to reduce measurement uncertainty was included. Feasibility data, suggested baseline functional descriptions of various types of active microwave sensors, and examples of existing radar techniques are summarized. Data manage and measurement processes are also covered.
It is well recognized that advection from the North Atlantic has a profound effect on the climatic conditions in central Europe. A new dataset of the ocean-surface winds, derived from the Special Sensor Microwave Imager, SSM/1, is now available. This satellite instrument measures the wind speed, but not the direction. However, variational analysis developed at the Data Assimilation Office, NASA Goddard Space Flight Center, by combining the SSM/I measurements with wind vectors measured from ships, etc., produced global maps of the ocean surface winds suitable for climate analysis. From this SSM/I dataset, a specific index I(sub na) of the North Atlantic surface winds has been developed, which pertinently quantifies the low-level advection into central Europe. For a selected time-period, the index I(sub na) reports the average of the amplitude of the wind, averaging only the speed when the direction is from the southwest (when the wind is from another direction, the contribution counts to the average as zero speed). Strong correlations were found between February I(sub na) and the surface air temperatures in Europe 50-60 deg N. In the present study, we present the correlations between I(sub na) and temperature I(sub s), and also the sensitivity of T(sub s), to an increase in I(sub na), in various seasons and various regions. We specifically analyze the flow of maritime-air from the North Atlantic that produced two extraordinary warm periods: February 1990, and early-winter 2000/2001. The very cold December 2001 was clearly due to a northerly flow. Our conclusion is that the SSM/I dataset is very useful for providing insight to the forcing of climatic fluctuations in Europe.
An assessment of a new source of vector wind stress data relative to existing analyses of the surface wind field is presented. The large-scale variability of vector wind stress generated by Atlas et al. (1991) and based on the special sensor microwave imager (SSM/I) remotely sensed observations of surface wind speed is compared with five operational and subjectively analyzed wind products across the tropical Pacific basin for the first year of SSM/I, July 1987 through June 1988. The spatial and temporal variability of the zonal component, meridional component, and curl of the wind stress are examined relative to their future use in wind-driven ocean model studies of tropical Pacific Ocean circulation.
Electronically scanned and fixed multiple beam phased arrays for spaceborne microwave radiometric sensors
Improved second generation wind algorithms are used to process the three month Seasat SMMR and SASS data sets. The new algorithms are derived without using in situ anemometer measurements. All known biases in the sensors prime measurements are removed, and the algorithms prime model functions are internally self-consistent. The computed SMMR and SASS winds are collocated and compared on a 10 km cell-by-cell basis, giving a total of 115444 wind comparisons. The comparisons are done using three different sets of SMMR channels. When the 6.6H SMMR channel is used for wind retrieval, the SMMR and SASS winds agree to within 1.3 m/s over the SASS primary swath. At nadir where the radar cross section is less sensitive to wind, the agreement degrades to 1.9 m/s. The agreement is very good for winds from 0 to 15 m/s. Above 15 m/s, the off-nadir SASS winds are consistently lower than the SMMR winds, while at nadir the high SASS winds are greater than SMMR's. When 10.7H is used for the SMMR wind channel, the SMMR/SASS wind comparisons are not quite as good. When the frequency of the wind channel is increased to 18 GHz, the SMMR/SASS agreement substantially degrades to about 5 m/S.