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NASA NTRS1982

SASS wind ambiguity removal by direct minimization

An objective analysis procedure is presented which combines Seasat-A satellite scatterometer (SASS) data with other available data on wind speeds by minimizing an objective function of gridded wind speed values. The functions are defined as the loss functions for the SASS velocity data, the forecast, the SASS velocity magnitude data, and conventional wind speed data. Only aliases closest to the analysis were included, and a method for improving the first guess while using a minimization technique and slowly changing the parameters of the problem is introduced. The model is employed to predict the wind field for the North Atlantic on Sept. 10, 1978. Dealiased SASS data is compared with available ship readings, showing good agreement between the SASS dealiased winds and the winds measured at the surface. Expansion of the model to take in low-level cloud measurements, pressure data, and convergence and cloud level data correlations is discussed.

Hoffman, R. N.↗
NASA NTRS1982

Intercomparison of wind speeds inferred by the SASS, altimeter, and SMMR

The operational theory, control algorithms, and comparisons with surface-determined wind speeds for the scatterometer (SASS), altimeter (ALT), and passive microwave radiometer (SMMR) on board the Seasat satellite are presented. Radiative scattering combining specular reflections and Bragg resonance scattering are noted to occur at tilting waves and sea foam, two conditions highly correlated with wind speed. SASS scans swaths of 70, 200, and 700 km from nadir, the SMMR covers a 150 km strip. Normalized radar sections are derived from the SASS and ALT telemetry, and brightness temperature from the SMMR. ALT winds were found to be biased about 3 m/sec low, while intercomparison between the SMMR and SASS data showed a mean difference of 0.3 m/sec with a standard deviation from measured winds of 1.7 m/sec or less. The effects of land thermal emissions, rain, and sun glint are discussed, and good viewing conditions are concluded to result in 2 m/sec accuracy.

Wentz, F. J.↗
NASA NTRS1982

SASS measurements of the Ku-band radar signature of the ocean

SeaSat-A Satellite Scatterometer (SASS) measurements of normalized radar cross section (NRCS) have been merged with high quality surface-wind fields based on in situ, to create a large data base of NRCS-wind signature data. These data are compared to the existing NRCS-wind model used by the SASS to infer winds. Falso-color maps of SASS NRCS and ocean winds from multiple orbits show important synoptic trends.

Schroeder, L. C.↗
NASA NTRS1980

The SASS scattering coefficient algorithm

This paper describes the algorithms used to convert engineering unit data obtained from the Seasat-A satellite scatterometer (SASS) to radar scattering coefficients and associated supporting parameters. A description is given of the instrument receiver and related processing used by the scatterometer to measure signal power backscattered from the earth's surface. The applicable radar equation used for determining scattering coefficient is derived. Sample results of SASS data processed through current algorithm development facility (ADF) scattering coefficient algorithms are presented which include scattering coefficient values for both water and land surfaces. Scattering coefficient signatures for these two surface types are seen to have distinctly different characteristics. Scattering coefficient measurements of the Amazon rain forest indicate the usefulness of this type of data as a stable calibration reference target.

Bracalente, E. M.↗
NASA NTRS1981

Determination of surface stress by Seasat-SASS - A case study with JASIN data

The values of sea surface stress determined with the dissipation method and those determined with a surface-layer model from observations on F.S. Meteor during the Joint Air-Sea Interaction (JASIN) Experiment are compared with the backscatter coefficients measured by the scatterometer SASS on the satellite Seasat. This study demonstrates that SASS can be used to determine surface stress directly as well as wind speed. The quality of the surface observations used in the calibration of the retrieval algorithms, however, is important. This sample of measurements disagrees with the predictions by the existing wind retrieval algorithm under non-neutral conditions and the discrepancies depend on atmospheric stability.

Liu, W. T.↗
NASA NTRS1980

SEASAT-A SASS wind processing

The techniques used for ingesting SEASAT-A SASS wind retrievals into the existing operational software are described. The intent is to assess the impact of SEASAT data in he marine wind fields produced by the global marine wind/sea level pressure analysis. This analysis is performed on a 21/2 deg latitude/longitude global grid which executes at three hourly time increments. Wind fields with and without SASS winds are being compared. The problems of data volume reduction and aliased wind retrieval ambiquity are treated.

Langland, R. A.↗
NASA NTRS1984

SASS wind forecast impact studies using the GLAS and NEPRF systems: Preliminary conclusions

For this project, a version of the GLAS Analysis/Forecast System was developed that includes an objective dealiasing scheme as an integral part of the analysis cycle. With this system the (100 sq km) binned SASS wind data generated by S. Peteherych of AER, Canada corresponding of the period 0000 GMT 7 September 1978 to 1200 GMT 13 September 1978 was objectively dealiased. The dealiased wind fields have been requested and received by JPL, NMC and the British Meteorological Office. The first 3.5 days of objectively dealiased fields were subjectively enhanced on the McIDAS system. Approximately 20% of the wind directions were modified, and of these, about 70% were changed by less than 90 deg. Two SASS forecast impact studies, were performed using the dealiased fields, with the GLAS and the NEPRF (Navy Environmental Prediction Research Facility) analysis/forecast systems.

Kalnay, E.↗
NASA NTRS1984

Synoptic scale wind field properties from the SEASAT SASS

Dealiased SEASAT SEASAT A Scatterometer System SASS vector winds obtained during the Gulf Of Alaska SEASAT Experiment GOASEX program are processed to obtain superobservations centered on a one degree by one degree grid. The grid. The results provide values for the combined effects of mesoscale variability and communication noise on the individual SASS winds. These superobservations winds are then processed further to obtain estimates of synoptic scale vector winds stress fields, the horizontal divergence of the wind, the curl of the wind stress and the vertical velocity at 200 m above the sea surface, each with appropriate standard deviations of the estimates for each grid point value. They also explain the concentration of water vapor, liquid water and precipitation found by means of the SMMR Scanning Multichannel Microwave Radiometer at fronts and occlusions in terms of strong warm, moist air advection in the warm air sector accompanied by convergence in the friction layer. Their quality is far superior to that of analyses based on conventional data, which are shown to yield many inconsistencies.

Pierson, W. J., Jr.↗
NASA NTRS1984

The effects of the variations in sea surface temperature and atmospheric stability in the estimation of average wind speed by SEASAT-SASS

The average wind speeds from the scatterometer (SASS) on the ocean observing satellite SEASAT are found to be generally higher than the average wind speeds from ship reports. In this study, two factors, sea surface temperature and atmospheric stability, are identified which affect microwave scatter and, therefore, wave development. The problem of relating satellite observations to a fictitious quantity, such as the neutral wind, that has to be derived from in situ observations with models is examined. The study also demonstrates the dependence of SASS winds on sea surface temperature at low wind speeds, possibly due to temperature-dependent factors, such as water viscosity, which affect wave development.

Liu, W. T.↗
NASA NTRS1984

A Monte Carlo comparison of the recovery of winds near upwind and downwind from the SASS-1 model function by means of the sum of squares algorithm and a maximum likelihood estimator

Backscatter measurements at upwind and crosswind are simulated for five incidence angles by means of the SASS-1 model function. The effects of communication noise and attitude errors are simulated by Monte Carlo methods, and the winds are recovered by both the Sum of Square (SOS) algorithm and a Maximum Likelihood Estimater (MLE). The SOS algorithm is shown to fail for light enough winds at all incidence angles and to fail to show areas of calm because backscatter estimates that were negative or that produced incorrect values of K sub p greater than one were discarded. The MLE performs well for all input backscatter estimates and returns calm when both are negative. The use of the SOS algorithm is shown to have introduced errors in the SASS-1 model function that, in part, cancel out the errors that result from using it, but that also cause disagreement with other data sources such as the AAFE circle flight data at light winds. Implications for future scatterometer systems are given.

Pierson, W. J., Jr.↗
NASA NTRS1984

SASS wind ambiguity removal by direct minimization. II - Use of smoothness and dynamical constraints

A variational analysis method (VAM) is used to remove the ambiguity of the Seasat-A Satellite Scatterometer (SASS) winds. The VAM yields the best fit to the data by minimizing an objective function S which is a measure of the lack of fit. The SASS data are described and the function S and the analysis procedure are defined. Analyses of a single ship report which are analogous to Green's functions are presented. The analysis procedure is tuned and its sensitivity is described using the QE II storm. The procedure is then applied to a case study of September 6, 1978, south of Japan.

Hoffman, R. N.↗
NASA NTRS1983

Highlights of the SEASAT-SASS program - A review

Some important concepts of the SEASAT-SASS program are described and some of the decisions made during the program as to methods for relating wind to backscatter are discussed. The radar scatterometer design is analyzed along with the model function, which is an empirical relationship between the backscatter value and the wind speed, wind direction, and incidence angle of the radar beam with the sea surface. The results of Monte Carlo studies of mesoscale turbulence and of studies of wind stress on the sea surface involving SASS are reviewed.

Pierson, W. J., Jr.↗
NASA NTRS1984

A SEASAT SASS simulation experiment to quantify the errors related to a + or - 3 hour intermittent assimilation technique

A series of SEASAT repeat orbits over a sequence of best Low center positions is simulated by using the Seatrak satellite calculator. These Low centers are, upon appropriate interpolation to hourly positions, Located at various times during the + or - 3 hour assimilation cycle. Error analysis for a sample of best cyclone center positions taken from the Atlantic and Pacific oceans reveals a minimum average error of 1.1 deg of Longitude and a standard deviation of 0.9 deg of Longitude. The magnitude of the average error seems to suggest that by utilizing the + or - 3 hour window in the assimilation cycle, the quality of the SASS data is degraded to the Level of the background. A further consequence of this assimilation scheme is the effect which is manifested as a result of the blending of two or more more juxtaposed vector winds, generally possessing different properties (vector quantity and time). The outcome of this is to reduce gradients in the wind field and to deform isobaric and frontal patterns of the intial field.

Sylvester, W. B.↗
NASA NTRS1999

Measurements of Nitric Acid and Aerosol Species Aboard the NASA DC-8 Aircraft During the SASS Ozone and Nitrogen Oxide Experiment (SONEX)

The SASS Ozone and Nitrogen Oxides Experiment (SONEX) over the North Atlantic during October/November 1997 offered an excellent opportunity to examine the budget of total reactive nitrogen (NO(sub y)) in the upper troposphere (8 - 12 km altitude). The median measured NO(sub y) mixing ratio was 425 parts per trillion by volume (pptv). Two different methods were used to measure HNO3: (1) the mist chamber technique and, (2) chemical ionization mass spectrometry. Two merged data sets using these HNO3 measurements were used to calculate NO(sub y) by summing the reactive nitrogen species (a combination of measured plus modeled results) and comparing the resultant values to measured NO(sub y) (gold catalytic reduction method). Both comparisons showed good agreement in the two quantities (slope > 0.9 and r(exp 2) > 0.9). Thus, the total reactive nitrogen budget in the upper troposphere over the North Atlantic can be explained in a general manner as a simple mixture of NO(sub x). (NO + NO2), HNO3, and PAN. Median values of NO(sub x)/NO(sub y) were approximately equal to 0.25, HNO3/NO(sub y) were approximately equal to 0.35 and Peroxyacetyl Nitrate (PAN)/NO(sub y) were approximately equal to 0. 17. Particulate NO3 and alkyl nitrates together composed <10 % of NO(sub y), while model estimated HNO4 averaged 12%.

Talbot, Robert W.↗
NASA NTRS1999

Measurements of Nitric Acid and Aerosol Species Aboard the NASA DC-8 Aircraft During the SASS OZone and Nitrogen Oxide Experiment (SONEX)

The SASS Ozone and Nitrogen Oxides Experiment (SONEX) over the north Atlantic during October/November 1997 offered an excellent opportunity to examine the budget of total reactive nitrogen (NO(y)) in the upper troposphere (8 - 12 km altitude). The median measured NO(y) mixing ratio was 425 parts per trillion by volume (pptv). Two different methods were used to measure HNO3: (1) the mist chamber technique and, (2) chemical ionization mass spectrometry. Two merged data sets using these HNO3 measurements were used to calculate NO(y) by summing the reactive nitrogen species (a combination of measured plus modeled results) and comparing the resultant values to measured NO(y) (gold catalytic reduction method). Both comparisons showed good agreement in the two quantities (slope greater than 0.9 and r(sup 2) greater than 0.9). Thus, the total reactive nitrogen budget in the upper troposphere over the North Atlantic can be explained in a general manner as a simple mixture of NO(x). (NO + NO2), HNO3, and PAN. Median values of NO(x)/NO(y) were approx. = 0.25, HNO3/NO(y) approx. = 0.35 and PAN/NO(y) approx. = 0.17. Particulate NO3 and alkyl nitrates together composed less than 10% of NO(y), while model estimated HNO4 averaged 12%.

Talbot, Robert W.↗
NASA NTRS1978

SeaSat-A Satellite Scatterometer (SASS) Validation and Experiment Plan

This plan was generated by the SeaSat-A satellite scatterometer experiment team to define the pre-and post-launch activities necessary to conduct sensor validation and geophysical evaluation. Details included are an instrument and experiment description/performance requirements, success criteria, constraints, mission requirements, data processing requirement and data analysis responsibilities.

Schroeder, L. C.↗
NASA NTRS1984

Vector wind, horizontal divergence, wind stress and wind stress curl from SEASAT-SASS at one degree resolution

Conventional data obtained in 1983 are contrasted with SEASAT-A scatterometer and scanning multichannel microwave radiometer (SMMR) data to show how observations at a single station can be extended to an area of about 150,000 square km by means of remotely sensed data obtained in nine minutes. Superobservations at a one degree resolution for the vector winds were estimated along with their standard deviations. From these superobservations, the horizontal divergence, vector wind stress, and the curl of the wind stress can be found. Weather forecasting theory is discussed and meteorological charts of the North Pacific Ocean are presented. Synoptic meteorology as a technique is examined.

Pierson, W. J., Jr.↗