W. Linwood Jones

NSCAT high-resolution surface wind measurements in Typhoon Violet

NASA scatterometer (NSCAT) measurements of the western Pacific Supertyphoon Violet are presented for revolutions 478 and 485 that occurred in September 1996. A tropical cyclone planetary boundary layer numerical model, which uses conventional meteorological and geostationary cloud data, is used to estimate the winds at 10-m elevation in the cyclone. These model winds are then compared with the winds inferred from the NSCAT backscatter data by means of a novel approach that allows a wind speed to be recovered from each individual backscatter cell. This spatial adaptive (wind vector) retrieval algorithm employs several unique steps. The backscatter values are first regrouped in terms of closest neighbors in sets of four. The maximum likelihood estimates of speed and direction are then used to obtain speeds and directions for each group. Since the cyclonic flow around the tropical cyclone is known, NSCAT wind direction alias selection is easily accomplished. The selected wind directions are then used to convert each individual backscatter value to a wind speed. The results are compared to the winds obtained from the tropical cyclone boundary layer model. The NSCAT project baseline geophysical model function, NSCAT 1, was found to yield wind speeds that were systematically too low, even after editing for suspected rain areas of the cyclone. A new geophysical model function was developed using conventional NSCAT data and airborne Ku band scatterometer measurements in an Atlantic hurricane. This new model uses the neural network method and yields substantially better agreement with the winds obtained from the boundary layer model according to the statistical tests that were used.

An Improved C-Band Ocean Surface Emissivity Model at Hurricane-Force Wind Speeds Over a Wide Range of Earth Incidence Angles

An improved microwave radiometric ocean surface emissivity model has been developed to support forward radiative transfer modeling of brightness temperature and geophysical retrieval algorithms for the next-generation airborne Hurricane Imaging Radiometer instrument. This physically based C-band emissivity model extends current model capabilities to hurricane-force wind speeds over a wide range of incidence angles. It was primarily developed using brightness temperature observations during hurricanes with coincident high-quality surface-truth wind speeds, which were obtained using the airborne Stepped-Frequency Microwave Radiometer. Also, other ocean emissivity models available through the published literature and the spaceborne WindSat radiometer measurements were used.

Spatial Variability of Surface Rainfall as Observed from TRMM Field Campaign Data

Abstract The spatial variability of surface rainfall over 5- and 30-day time periods is observed, and it is found that the spatial decorrelation length of precipitation is comparable to the size of a single surface gauge network. The observed variability is found to affect radar-derived precipitation estimation, particularly if it is based on calibration using rain gauges. The radar subgrid-scale variability is also observed using some redundant and finer-scale gauge networks deployed during the Tropical Rainfall Measuring Mission (TRMM) ground-validation field campaigns. Based upon statistical analysis and a point-based decision-making system, a best-suited spatial–temporal filtering technique is suggested and, when applied to match radar data with any other surface observation, is found to reduce bias.

The hurricane imaging radiometer - an octave bandwidth synthetic thinned array radiometer

The Hurricane Imaging Radiometer (HIRad) is a new airborne sensor that is currently under development. It is intended to produce wide-swath images of ocean surface wind speed and near surface rain rate in hurricanes conditions. HIRad will extend the scientific capabilities and technologies associated with two previous successful airborne microwave radiometers: the real aperture Stepped Frequency Microwave Radiometer (SFMR) and the synthetic aperture Lightweight Rainfall Radiometer (LRR). Both SFMR and HIRad are required to operate over the full C-Band octave in order to estimate precipitation levels experienced in hurricanes without saturation and to penetrate through the precipitation and estimate surface winds. Operation over an octave bandwidth was easily accomplished by the nadir-pointing horn antenna used by SFMR. However, it represents a major technological challenge for the HIRad design because it is a Fourier synthesis imager. Details of how HIRad meets that challenge are described here.

Correction of Time-Varying Radiometric Errors in TRMM Microwave Imager Calibrated Brightness Temperature Products

This letter presents an empirical correction for a time-varying radiometric calibration error (2.5 K peak to peak) present in the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) 1B11 calibrated brightness temperature (Tb) data product. The Tb error is modeled as a function of the spacecraft orbit position and the Sun elevation above the orbit plane (solar beta angle) based on the observed systematic differences between the TMI 10-GHz vertically polarized (10-V) channel oceanic Tbs as compared to a radiative transfer model with collocated numerical weather model environmental parameters. Assuming a slightly emissive reflector, the errors in the other TMI channels are estimated from the 10-GHz error model. This method is evaluated using before- and after-correction comparisons of 1B11 data over the ocean and Amazon, and results show that this method effectively eliminates the time-varying calibration error. This correction technique will be implemented in version 7 of the TRMM 1B11 data product, which is scheduled to be released in 2010.

Investigation of rain effects on Aquarius Sea Surface Salinity measurements

The Aquarius/SAC-D mission has been providing Sea Surface Salinity (SSS), globally over the ocean, for almost 3 years. As a member of the AQ/SAC-D Cal/Val team, the Central Florida Remote Sensing Laboratory has analyzed these salinity retrievals in the presence of rain and has noted the strong correlation between the spatial patterns of reduced SSS and the spatial distribution of rainfall. It was determined that this is the result of a cause and effect relationship, as opposed to SSS measurement errors. Hence, it is important to understand these SSS changes due to seawater dilution by rain and the associated near-surface salinity stratification. This paper addresses the effects of rainfall on the Aquarius (AQ) SSS retrieval using a macro-scale Rain Impact Model (RIM) in the region of high convective rain over the Inter-tropical Convergence Zone. This model, based on the superposition of a one-dimension eddy diffusion (turbulent diffusion) model, relates sea surface salinity to depth, rain accumulation and time since rainfall. For aiding in the identification of instantaneous and prior rainfall accumulations, an AQ Rain Accumulation product was developed. This product, based on the NOAA CMORPH rain data set, provides the rainfall history for 24 h prior to the observation time, which is integrated over each AQ SSS measurement cell. In this paper results of the RIM validation are presented by comparing AQ measured and RIM simulated SSS for several months of 2012. Results show the high cross correlation for these comparisons and also with the corresponding SSS anomalies relative to HYCOM.

NSCAT normalized radar backscattering coefficient biases using homogenous land targets

The NASA scatterometer (NSCAT) is a spaceborne radar sensor designed to measure the normalized radar backscattering coefficient σ0 of the Earths surface. Over the ocean, backscatter measurements are used to infer surface wind vectors. Wind retrieval is based on a statistical relationship between short-ocean wave roughness (that causes the backscatter) and the surface wind speed and direction. For NSCAT geometry, multiple antennas are used to provide backscatter measurements at several azimuth directions to resolve wind direction ambiguities. To achieve the desired wind vector accuracy, these antenna beams must be calibrated within a few tenths of a decibel. A simple relative-calibration method is applied to the NASA scatterometer backscatter from homogenous, isotropic, large-area targets. These targets exhibit both azimuth and time invariant radar response. A simple polynomial model for incidence angle dependence of σ0 is used, and the mean radar response from all antenna beams is taken as the reference. Corrections (σ0 biases) are calculated as differences (in log space) between measurements from particular beam and the reference. This simple model is applied to data from the Amazon rain forest and the Siberian plain. These areas are tested for temporal stability within the calibration period (several weeks). High-resolution masks are applied to extract suitable calibration data sets. Calculated corrections for each antenna beam are added to NSCAT σ0 measurements as a function of incidence angle. The magnitudes of corrections show the necessity of on-orbit calibration.

Intercalibration of the GPM Microwave Radiometer Constellation

AbstractThe Global Precipitation Measurement (GPM) mission is a constellation-based satellite mission designed to unify and advance precipitation measurements using both research and operational microwave sensors. This requires consistency in the input brightness temperatures (Tb), which is accomplished by intercalibrating the constellation radiometers using the GPM Microwave Imager (GMI) as the calibration reference. The first step in intercalibrating the sensors involves prescreening the sensor Tb to identify and correct for calibration biases across the scan or along the orbit path. Next, multiple techniques developed by teams within the GPM Intersatellite Calibration Working Group (XCAL) are used to adjust the calibrations of the constellation radiometers to be consistent with GMI. Comparing results from multiple approaches helps identify flaws or limitations of a given technique, increase confidence in the results, and provide a measure of the residual uncertainty. The original calibration difference...

Improved Hurricane Ocean Vector Winds Using SeaWinds Active/Passive Retrievals

The SeaWinds scatterometer, onboard the QuikSCAT satellite, infers global ocean vector winds (OVWs); however, for a number of reasons, these measurements in hurricanes are significantly degraded. This paper presents an improved hurricane OVW retrieval approach, known as Q-Winds, which is derived from combined SeaWinds active and passive measurements. In this technique, the effects of rain are implicitly included in a new geophysical model function, which relates oceanic brightness temperature and radar backscatter measurements (at the top of the atmosphere) to the surface wind vector under both clear sky and in the presence of light to moderate rain. This approach extends the useful wind speed measurement range for tropical cyclones beyond that exhibited by the standard SeaWinds Project Level-2B (L2B) 12.5-km wind vector algorithm. A description of the Q-Winds algorithm is given, and examples of OVW retrievals are presented for the Q-Winds and L2B 12.5-km algorithms for ten hurricane overpasses in 2003-2008. These data are also compared to independent surface wind vector estimates from the National Oceanic and Atmospheric Administration Hurricane Research Divisions objective hurricane surface wind analysis technique known as H*Wind. These comparisons suggest that the Q-Winds OVW product agrees better with independently derived H^ Wind analysis winds than does the conventional L2B OVW product.

A Consensus Calibration based on TMI and Windsat

The Global Precipitation Measurement (GPM) mission requires a high degree of consistency among the microwave radiometers in the constellation which, in turn, demands a standard against which all the sensors can be compared. Ultimately this standard will be the GPM Microwave Imager, but for the present the TRMM Microwave Imager (TMI) fills this need. Since its calibration leaves much to be desired, a refinement using Windsat has been developed. This article defines the Consensus Calibration 1.1 which is applied to the TMI. In turn the TMI serves as a transfer standard to other satellite radiometers.