Engineering topics

Wentz, F.

Publications and source records attributed to Wentz, F..

12 records

NASA NTRS2017

Status of Remote Sensing of Salinity by Aquarius

Aquarius is an L-band instrument designed to measure sea surface salinity from space. The instrument was launched in 2011 and data acquisition ended in June 2015 when control of the spacecraft was lost. Aquarius produced global maps of salinity with accuracy of 0.2 psu (Practical Salinity Unit) and special resolution of 150 kilometers as well as other products such as global maps of RFI (Radio Frequency Interference) and soil moisture. The mission will formally end December 2017.

Le Vine, D. M.↗

NASA NTRS2015

Remote Sensing of Salinity and Overview of Results from Aquarius

Aquarius is a combined active/passive microwave (L-band) instrument designed to map the salinity of global oceans from space. The specific goal of Aquarius is to monitor the seasonal and interannual variation of the large scale features of the sea surface salinity (SSS) field of the open ocean (i.e. away from land). The instrumentation has been designed to provide monthly maps with a spatial resolution of 150 km and an accuracy of 0.2 psu

Microwave Remote Sensing↗

NASA NTRS2014

Aquarius Radiometer Status

Aquarius was launched on June 10, 2011 as part of the Aquarius/SAC-D observatory and the instrument has been operating continuously since being turned on in August of the same year. The initial map of sea surface salinity was released one month later (September) and the quality of the retrieval has continuously improved since then. The Aquarius radiometers include several special features such as measurement of the third Stokes parameter, fast sampling, and careful thermal control, and a combined passive/active instrument. Aquarius is working well and in addition to helping measure salinity, the radiometer special features are generating new results.

Mircrowave Remote Sensing↗

NASA NTRS2012

Aquarius: The Instrument and Initial Results

Aquarius was launched on June 10, 2011 aboard the Aquarius/SAC-D observatory and the instrument has been operating continuously since the initial turned-on was completed on August 25. The initial observed antenna temperatures were close to predicted and the first salinity map was released in September. In order to map the ocean salinity field, Aquarius includes several special features such as the inclusion of a scatterometer to provide a roughness correction, measurement of the third Stokes parameter to correct for Faraday rotation, and fast sampling to mitigate the effects of RFI. This paper provides an overview of the instrument and an example of initial results. Details are covered in subsequent papers in the session on Aquarius

Ocean salinity↗

NASA NTRS2012

Ocean Surface Emissivity at L-band (1.4 GHz): The Dependence on Salinity and Roughness

A characterization of the emissivity of sea water at L-band is important for the remote sensing of sea surface salinity. Measurements of salinity are currently being made in the radio astronomy band at 1.413 GHz by ESA's Soil Moisture and Ocean Salinity (SMOS) mission and NASA's Aquarius instrument aboard the Aquarius/SAC-D observatory. The goal of both missions is accuracy on the order of 0.1 psu. This requires accurate knowledge of the dielectric constant of sea water as a function of salinity and temperature and also the effect of waves (roughness). The former determines the emissivity of an ideal (i.e. flat) surface and the later is the major source of error from predictions based on a flat surface. These two aspects of the problem of characterizing the emissivity are being addressed in the context of the Aquarius mission. First, laboratory measurements are being made of the dielectric constant of sea water. This is being done at the George Washington University using a resonant cavity. In this technique, sea water of known salinity and temperature is fed into the cavity along its axis through a narrow tube. The sea water changes the resonant frequency and Q of the cavity which, if the sample is small enough, can be related to the dielectric constant of the sample. An extensive set of measurements have been conducted at 1.413 GHz to develop a model for the real and imaginary part of the dielectric constant as a function of salinity and temperature. The results are compared to the predictions of models based on parameterization of the Debye resonance of the water molecule. The models and measurements are close; however, the differences are significant for remote sensing of salinity. This is especially true at low temperatures where the sensitivity to salinity is lowest.

LeVine, D. M.↗

NASA NTRS1999

The Status of the Tropical Rainfall Measuring Mission (TRMM) after 2 Years in Orbit

The Tropical Rainfall Measuring Mission (TRMM) satellite was launched on November 27, 1997, and data from all the instruments first became available approximately 30 days after launch. Since then, much progress has been made in the calibration of the sensors, the improvement of the rainfall algorithms, in related modeling applications and in new datasets tailored specifically for these applications. This paper reports the latest results regarding the calibration of the TRMM Microwave Imager, (TMI), Precipitation Radar (PR) and Visible and Infrared Sensor (VIRS). For the TMI, a new product is in place that corrects for a still unknown source of radiation leaking in to the TMI receiver. The PR calibration has been adjusted upward slightly (by 0.6 dBZ) to better match ground reference targets, while the VIRS calibration remains largely unchanged. In addition to the instrument calibration, great strides have been made with the rainfall algorithms as well, with the new rainfall products agreeing with each other to within less than 20% over monthly zonally averaged statistics. The TRMM Science Data and Information System (TSDIS) has responded equally well by making a number of new products, including real-time and fine resolution gridded rainfall fields available to the modeling community. The TRMM Ground Validation (GV) program is also responding with improved radar calibration techniques and rainfall algorithms to provide more accurate GV products which will be further enhanced with the new multiparameter 10 cm radar being developed for TRMM validation and precipitation studies. Progress in these various areas has, in turn, led to exciting new developments in the modeling area where Data Assimilation, and Weather Forecast models are showing dramatic improvements after the assimilation of observed rainfall fields.

Kummerow, C.↗

NASA NTRS1995

An atlas of monthly mean distributions of SSMI surface wind speed, AVHRR/2 sea surface temperature, AMI surface wind velocity, TOPEX/POSEIDON sea surface height, and ECMWF surface wind velocity during 1993

The following monthly mean global distributions for 1993 are presented with a common color scale and geographical map: 10-m height wind speed estimated from the Special Sensor Microwave Imager (SSMI) on a United States (U.S.) Air Force Defense Meteorological Satellite Program (DMSP) spacecraft; sea surface temperature estimated from the Advanced Very High Resolution Radiometer (AVHRR/2) on a U.S. National Oceanic and Atmospheric Administration (NOAA) satellite; 10-m height wind speed and direction estimated from the Active Microwave Instrument (AMI) on the European Space Agency (ESA) European Remote Sensing (ERS-1) satellite; sea surface height estimated from the joint U.S.-France Topography Experiment (TOPEX)/POSEIDON spacecraft; and 10-m height wind speed and direction produced by the European Center for Medium-Range Weather Forecasting (ECMWF). Charts of annual mean, monthly mean, and sampling distributions are displayed.

Halpern, D.↗

NASA NTRS1993

An atlas of monthly mean distributions of SSMI surface wind speed, ARGOS buoy drift, AVHRR/2 sea surface temperature, and ECMWF surface wind components during 1991

The following monthly mean global distributions for 1991 are presented with a common color scale and geographical map: 10-m height wind speed estimated from the Special Sensor Microwave Imager (SSMI) on a United States Air Force Defense Meteorological Satellite Program (DMSP) spacecraft; sea surface temperature estimated from the advanced very high resolution radiometer (AVHRR/2) on a U.S. National Oceanic and Atmospheric Administration (NOAA) spacecraft; Cartesian components of free-drifting buoys which are tracked by the ARGOS navigation system on NOAA satellites; and Cartesian components of the 10-m height wind vector computed by the European Center for Medium-Range Weather Forecasting (ECMWF). Charts of monthly mean value, sampling distribution, and standard deviation value are displayed. Annual mean distributions are displayed.

Halpern, D.↗

NASA NTRS1993

An atlas of monthly mean distributions of SSMI surface wind speed, ARGOS buoy drift, AVHRR/2 sea surface temperature, and ECMWF surface wind components during 1990

The following monthly mean global distributions for 1990 are proposed with a common color scale and geographical map: 10-m height wind speed estimated from the Special Sensor Microwave Imager (SSMI) on a United States (US) Air Force Defense Meteorological Satellite Program (DMSP) spacecraft; sea surface temperature estimated from the advanced very high resolution radiometer (AVHRR/2) on a U.S. National Oceanic and Atmospheric Administration (NOAA) spacecraft; Cartesian components of free drifting buoys which are tracked by the ARGOS navigation system on NOAA satellites; and Cartesian components on the 10-m height wind vector computed by the European Center for Medium-Range Weather Forecasting (ECMWF). Charts of monthly mean value, sampling distribution, and standard deviation values are displayed. Annual mean distributions are displayed.

Halpern, D.↗

NASA NTRS1993

Geophysics, Oceanography

Development of decade-long time series of global surface wind measurements for studies ofseasonal-to-interannual climate variability presents unique challenges for space- borne instrumentationbecause of the necessity to combine data sets of 3- to 5-year lifetimes. Before the first Special SensorMicrowave Imager (SSMI), which was launched on the Defence Meteorological Satellite Program(DMSP) F8 spacecraft in July 1987, stopped recording wind speed in December 1991, another SSMIwas launched on DMSP F10 in December 1991. Interpretation of the 1987 - 1993 composite timeseries is dependent upon the space and time characteristics of the differences between concurrent F8and F10 SSMI measurements. This paper emphasizes large geographical regions and 1-month timescale. The F8-F10 area-weighted difference between 60 degrees S and 60 degrees S during 305 daysof 1991 (-0.12 m s^(-1)) was comparable to the year-to-year wind speed variations during 1988-1991. The 10 degree-zonal averaged monthly mean F8-F10 difference was negative (positive) forwind speeds less (greater) than 7.9 m s^(-1), reaching - 0.43(0.32) m s^(-1) at 5(10) m s^(-1). The10 degree-zonal averaged monthly mean F8-F10 bias had considerable variations throughout the yearand between 60 degrees S - 60 degrees N, with the largest temporal variation (1.4 m s^(-1)) in the 50degrees - 60 degrees N region from February to April. The 1991 average value of the monthly meanroot-mean-square (rms) difference between F8 and F10 daily wind speeds in 10 degree-longitudinalbands was 2.0 m s^(-1) over 60 degrees S - 60 degrees N, the amplitude of the annual cycle of therms difference was largest in the northern hemisphere middle latitudes, and the rms difference wasrelated to the wind speed (e.g., at 6 and 10 m s^(-1), the rms difference was 1.7 and 2.7 m s^(-1),respectively). The relationship between monthly mean 1/3 degrees x 1/3 degrees F8-F10 SSMI windspeed differences and integrated water vapor and liquid water content in the atmosphere is discussed.

Halpern, D.↗

NASA NTRS1993

On the Problem of Measuring Interannual Wind Speed Variations Using SSMI Data

The first Special Sensor Microwave Imager (SSMI) was launched on the Defence 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.

SSMI↗

NASA NTRS1991

An atlas of monthly mean distributions of GEOSAT sea surface height, SSMI surface wind speed, AVHRR/2 sea surface temperature, and ECMWF surface wind components during 1988

Monthly mean global distributions for 1988 are presented with a common color scale and geographical map. Distributions are included for sea surface height variation estimated from GEOSAT; surface wind speed estimated from the Special Sensor Microwave Imager on the Defense Meteorological Satellite Program spacecraft; sea surface temperature estimated from the Advanced Very High Resolution Radiometer on NOAA spacecrafts; and the Cartesian components of the 10m height wind vector computed by the European Center for Medium Range Weather Forecasting. Charts of monthly mean value, sampling distribution, and standard deviation value are displayed. Annual mean distributions are displayed.

Halpern, D.↗