Engineering topics
Wentz, Frank
Publications and source records attributed to Wentz, Frank.
The Aquarius Salinity Retrieval Algorithm
The first part of this presentation gives an overview over the Aquarius salinity retrieval algorithm. The instrument calibration [2] converts Aquarius radiometer counts into antenna temperatures (TA). The salinity retrieval algorithm converts those TA into brightness temperatures (TB) at a flat ocean surface. As a first step, contributions arising from the intrusion of solar, lunar and galactic radiation are subtracted. The antenna pattern correction (APC) removes the effects of cross-polarization contamination and spillover. The Aquarius radiometer measures the 3rd Stokes parameter in addition to vertical (v) and horizontal (h) polarizations, which allows for an easy removal of ionospheric Faraday rotation. The atmospheric absorption at L-band is almost entirely due to molecular oxygen, which can be calculated based on auxiliary input fields from numerical weather prediction models and then successively removed from the TB. The final step in the TA to TB conversion is the correction for the roughness of the sea surface due to wind, which is addressed in more detail in section 3. The TB of the flat ocean surface can now be matched to a salinity value using a surface emission model that is based on a model for the dielectric constant of sea water [3], [4] and an auxiliary field for the sea surface temperature. In the current processing only v-pol TB are used for this last step.
Aquarius Radiometer Performance: Early On-Orbit Calibration and Results
The Aquarius/SAC-D observatory was launched into a 657-km altitude, 6-PM ascending node, sun-synchronous polar orbit from Vandenberg, California, USA on June 10, 2011. The Aquarius instrument was commissioned two months after launch and began operating in mission mode August 25. The Aquarius radiometer meets all engineering requirements, exhibited initial calibration biases within expected error bars, and continues to operate well. A review of the instrument design, discussion of early on-orbit performance and calibration assessment, and investigation of an on-going calibration drift are summarized in this abstract.
Highlights of the First 15 Months of Aquarius Salinity Measurements
Aquarius satellite salinity measurements are resolving the major global and regional spatial patterns, and temporal variations, since the start of routine data collection on 25 August 2011. This description includes the principal seasonal variations over the first annual cycle as observed by the mission. In particular, we identify the evolution of low salinity anomalies associated with the Atlantic and Pacific intertropical convergence zones (ITCZ), major river outflows such as the Amazon, a seasonal low salinity anomaly in the Panama bight, and other features. We also explore the links that the salinity variations have with precipitation and surface currents. We then will describe the variations related to the presently evolving 2012 El Nino, now evident, as it progresses through the summer and fall 2012. We conclude with a brief summary of the Aquarius data products and validation
A Sample of What We Have Learned from A-Train Cloud Measurements
The A-train active sensors CloudSat and CALIPSO provide detailed information about cloud vertical structure. Coarse vertical information can also be obtained from a combination of passive sensors (e.g. cloud liquid water content from AMSR-E, cloud ice properties from MLS and HIRDLS, cloud-top pressure from MODIS and AIRS, and UVNISINear IR absorption and scattering from OMI, MODIS, and POLDER). In addition, the wide swaths of instruments such as MODIS, AIRS, OMI, POLDER, and AMSR-E can be exploited to create estimates of the three-dimensional cloud extent. We will show how data fusion from A-train sensors can be used, e.g., to detect and map the presence of multiple layer/phase clouds. Ultimately, combined cloud information from Atrain instruments will allow for estimates of heating and radiative flux at the surface as well as UV/VIS/Near IR trace-gas absorption at the overpass time on a near-global daily basis. CloudSat has also dramatically improved our interpretation of visible and UV passive measurements in complex cloudy situations such as deep convection and multiple cloud layers. This has led to new approaches for unique and accurate constituent retrievals from A-train instruments. For example, ozone mixing ratios inside tropical deep convective clouds have recently been estimated using the Aura Ozone Monitoring Instrument (OMI). Field campaign data from TC4 provide additional information about the spatial variability and origin of trace-gases inside convective clouds. We will highlight some of the new applications of remote sensing in cloudy conditions that have been enabled by the synergy between the A-train active and passive sensors.
Science Data Processing for the Advanced Microwave Scanning Radiometer: Earth Observing System
The National Aeronautics and Space Administration established the framework for the Science Investigator-led Processing Systems (SIPS) to enable the Earth science data products to be produced by personnel directly associated with the instrument science team and knowledgeable of the science algorithms. One of the first instantiations implemented for NASA was the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) SIPS. The AMSR-E SIPS is a decentralized, geographically distributed ground data processing system composed of two primary components located in California and Alabama. Initial science data processing is conducted at Remote Sensing Systems (RSS) in Santa Rosa, California. RSS ingests antenna temperature orbit data sets from JAXA and converts them to calibrated, resampled, geolocated brightness temperatures. The brightness temperatures are sent to the Global Hydrology and Climate Center in Huntsville, Alabama, which generates the geophysical science data products (e.g., water vapor, sea surface temperature, sea ice extent, etc.) suitable for climate research and applications usage. These science products are subsequently sent to the National Snow and Ice Data Center Distributed Active Archive Center in Boulder, Colorado for archival and dissemination to the at-large science community. This paper describes the organization, coordination, and production techniques employed by the AMSR-E SIPS in implementing, automating and operating the distributed data processing system.
ECMWF and SSM/I global surface wind speeds
Monthly mean 2.5 deg x 2.5 deg resolution 10-m height wind speeds from the Special Sensor Microwave/Imager (SSM/I) instrument and the European Centre for Medium-Range Weather Forecasts (ECMWF) forecast-analysis system are compared between 60 deg S and 60 deg N during 1988-91. The SSM/I data were uniformly processed while numerous changes were made to the ECMWF forecast-analysis system. The SSM/I measurements, which were compared with moored-buoy wind observations, were used as a reference dataset to evaluate the influence of the changes made to the ECMWF system upon the ECMWF surface wind speed over the ocean. A demonstrable yearly decrease of the difference between SSM/I and ECMWF wind speeds occurred in the 10 deg S-10 deg N region, including the 5 deg S-5 deg N zone of the Pacific Ocean, where nearly all of the variations occurred in the 160 deg E-160 deg W region. The apparent improvement of the ECMWF wind speed occurred at the same time as the yearly decrease of the equatorial Pacific SSM/I wind speed, which was associated with the natural transition from La Nina to El Nino conditions. In the 10 deg S-10 deg N tropical Atlantic, the ECMWF wind speed had a 4-yr trend, which was not expected nor was it duplicated with the SSM/I data. No yearly trend was found in the difference between SSM/I and ECMWF surface wind speeds in middle latitudes of the Northern and Southern Hemispheres. The magnitude of the differences between SSM/I and ECMWF was 0.4 m/s or 100% larger in the Northern than in the Southern Hemisphere extratropics. In two areas (Arabian Sea and North Atlantic Ocean) where ECMWF and SSM/I wind speeds were compared to ship measurements, the ship data had much better agreement with the ECMWF analyses compared to SSM/I data. In the 10 deg S-10 deg N area the difference between monthly standard deviations of the daily wind speeds dropped significantly from 1988 to 1989 but remained constant at about 30% for the remaining years.
On the problem of measuring interannual wind speed variations using SSMI data
The first Special Sensor Microwave Imager (SSMI) was launched on the Defense Meteorological Satellite Program (DMSP) F8 spacecraft in July 1987, and wind speed was no longer retrieved after December 1991. A second SSMI was launched on DMSP F10 in December 1990. Interpretation of the 1987-1993 (or longer) SSMI wind speed time series is dependent upon the space and time characteristics of the differences between F8 and F10 SSMI measurements. The 10 deg-zonal averaged monthly mean F8-F10 wind speed difference was negative (positive) for wind speeds less (greater) than 7.9 m/s, reaching -0.43 (0.32) m/s at 5(10) m/s. Between 60 deg S and 60 deg N the 10 deg-zonal averaged monthly mean F8-F10 wind speed bias was greater than +/- 0.5 m/s on several occasions. From 60 deg S - 60 deg N the 1991 average value of the monthly mean root-mean-square difference between daily F8 and F10 wind speeds in 10 deg-longitudinal bands was 2.0 m/s.In the 60 deg S - 60 deg N region, about 50% of the daily F8 and F10 wind speed differences was caused by measurement non-simultaneity and about 50% of the difference was attributed to other factors, such as instrument noise and the different azimuthal orientations of each SSMI.
ECMWF and SSMI Global Surface Wind Speeds
Monthly mean, 2.5 deg - x 2.5 deg-resolution, 10-m height wind speeds from the Special Sensor Microwave Imager (SSMI) instrument and the European Center for Medium-Range Weather Forecasts (ECMWF) forecast-analysis system are compared between 60 deg S and 60 deg N during 1988-1991. The SSMI data were uniformly processed while numerous changes were made to the ECMWF forecast-analysis system. The SSMI measurements, which were compared with moored-buoy wind observations, were considered to be a reference data set to evaluate the influence of the changes made to the ECMWF system upon the ECMWF surface wind speed over the ocean. A demonstrable yearly decrease of the difference between SSMI and ECMWF wind speeds occurred in the 10 deg S - 10 deg N region, including the 5 deg S - 5 deg N zone of the Pacific Ocean, where nearly all of the variations occurred in the 160 deg E - 160 deg W region. The apparent improvement of the ECMWF wind speed occurred at the same time as the yearly decrease of the equatorial Pacific SSMI wind speed, which was associated with the natural transition from La Nina to El Nino conditions. In the 10 deg S - 10 deg N tropical Atlantic, the ECMWF wind speed had a 4-year trend, which was not expected nor was it duplicated with the SSMI data. No yearly trend was found in the difference between SSMI and ECMWF surface wind speeds in middle latitudes of the northern and southern hemispheres. The magnitude of the differences between SSMI and ECMWF was 0.4 m s^(-1) or 100 percent larger in the northern than in the southern hemisphere extratropics. In two areas (Arabian Sea and North Atlantic Ocean) where ECMWF and SSMI wind speeds were compared to ship measurements, the ship data had much better agreement with the ECMWF analyses compared to SSMI data. In the 10 deg S - 10 deg N area the difference between monthly standard deviations of the daily wind speeds dropped significantly from 1988 to 1989, but remained constant at about 30 percent for the remaining years. y.
Recent improvements in Geosat altimeter data
Techniques are described for enhancing the accuracy of the geophysical data records derived from Geosat altimeter observations with treatments for water-vapor correction and satellite orbit. The TOVS/Special Sensor Microwave Imager (SSMI) water vapor data and T2 ephemeris are used to effectively adjust tide-gauge records. The T2 orbit is found to be effective for the study of large-scale phenomena with reductions in the radial orbit error.