William G. Pichel

The development and operational application of nonlinear algorithms for the measurement of sea surface temperatures with the NOAA polar-orbiting environmental satellites

Since 1990, the NOAA National Environmental Satellite Data and Information Service (NESDIS) has provided satellite-derived sea surface temperature (SST) measurements based on nonlinear SST algorithms, using advanced very high resolution radiometer (AVHRR) multiple-infrared window channel data. This paper develops linear and nonlinear SST algorithms from the radiative transfer equation. It is shown that the nonlinear algorithms are more accurate than linear algorithms but that the functional dependence of the nonlinearity is data dependent. This theoretical discussion (sections 2–4) is followed with a discussion in section 5 of the accuracy over a 9-year period of the satellite-derived SST measurements provided by NOAA NESDIS when compared with coincident drifting buoys. Between 1989 and 1998 the global scatter of the daytime satellite SST against drifting buoy measurements has decreased from ∼0.8° to 0.5°C, while the nighttime scatter has remained fairly constant at 0.5°C. An exception to these accuracy measurements occurred after the eruption of Mount Pinatubo in June 1991.

Comparison of SAR-derived wind speed with model predictions and ocean buoy measurements

As part of the Alaska synthetic aperture radar (SAR) Demonstration Project in 1999 and 2000, wide-swath RADARSAT SAR imagery has been acquired on a regular basis in the Gulf of Alaska and the Bering Sea. During 1998 and 1999, similar data were acquired off the East Coast of the United States as part of the StormWatch Project. The radar cross section measurements from these images were combined with wind direction estimates from the Navy Operational Global Atmospheric Prediction System model to produce high-resolution maps of the surface wind speed. For this study, 2862 SAR image frames were collected and examined. Averaged wind estimates from this data base have been systematically compared with corresponding wind speed estimates from buoy measurements and model predictions, and very good agreement has been found. The standard deviation between the buoy wind speed and the SAR estimates is 1.76 m/s. Details of the SAR wind extraction procedure are discussed, along with implications of the comparisons on the C-band polarization ratio.

Multi-channel improvements to satellite-derived global sea surface temperatures

Abstract High-quality multispectral measurements from satellites, and the recent development of multiple-window techniques to correct infrared brightness temperatures for atmospheric attenuation, have enabled marked improvements in global mapping of sea surface temperatures. The 4-km resolution data are in two visual bands and three atmospheric windows in the thermal infrared from the advanced Very High Resolution Radiometer (AVHRR) on NOAAs operational polar satellites. Various threshold and/or spatial homogeniety tests are applied to small data arrays to discriminate nominally cloud-free samples for subsequent processing. Tests of the multi-channel equations against independent buoy data gave bias = 0.42C and scatter = 0.62C. Global statistical comparisons with ships indicate significant improvements in accuracy and coverage over previous satellite-derived surface temperatures.

A systematic comparison of QuikSCAT and SAR ocean surface wind speeds

We performed a systematic comparison of wind speed measurements from the SeaWinds QuikSCAT scatterometer and wind speeds computed from RADARSAT-1 synthetic aperture radar (SAR) normalized radar cross section measurements. These comparisons were made over in the Gulf of Alaska and extended over a two-year period, 2000 and 2001. The SAR wind speed estimates require a wind direction to initialize the retrieval. Here, we first used wind directions from the Navy Operational Global Atmospheric Prediction System (NOGAPS) model. For these retrievals, the standard deviation between the resulting SAR and QuikSCAT wind speed measurements was 1.78 m/s. When we used the QuikSCAT-measured wind directions to initialize the inversion, comparisons improve to a standard deviation of 1.36 m/s. We used these SAR-scatterometer comparisons to generate a new C-band horizontal polarization model function. With this new model function, the wind speed inversion improves to a standard deviation of 1.24 m/s with no mean bias. These results strongly suggest that SAR and QuikSCAT measurements can be combined to make better high-resolution wind measurements than either instrument could alone in coastal areas.

Validation of coastal sea and lake surface temperature measurements derived from NOAA/AVHRR data

An interactive validation monitoring system is being used at the NOAA/NESDIS to validate the sea surface temperature (SST) derived from the NOAA-12 and NOAA-14 polar orbiting satellite AVHRR sensors for the NOAA CoastWatch program. In 1997, we validated the SST in coastal regions of the Gulf of Mexico, Southeast US and Northeast US and the lake surface temperatures in the Great Lakes every other month. The in situ

SAR observation and model tracking of an oil spill event in coastal waters.

Oil spills are a major contributor to marine pollution. The objective of this work is to simulate the oil spill trajectory of oil released from a pipeline leaking in the Gulf of Mexico with the GNOME (General NOAA Operational Modeling Environment) model. The model was developed by NOAA (National Oceanic and Atmospheric Administration) to investigate the effects of different pollutants and environmental conditions on trajectory results. Also, a Texture-Classifying Neural Network Algorithm (TCNNA) was used to delineate ocean oil slicks from synthetic aperture radar (SAR) observations. During the simulation, ocean currents from NCOM (Navy Coastal Ocean Model) outputs and surface wind data measured by an NDBC (National Data Buoy Center) buoy are used to drive the GNOME model. The results show good agreement between the simulated trajectory of the oil spill and synchronous observations from the European ENVISAT ASAR (Advanced Synthetic Aperture Radar) and the Japanese ALOS (Advanced Land Observing Satellite) PALSAR (Phased Array L-band Synthetic Aperture Radar) images. Based on experience with past marine oil spills, about 63.0% of the oil will float and 18.5% of the oil will evaporate and disperse. In addition, the effects from uncertainty of ocean currents and the diffusion coefficient on the trajectory results are also studied.

Using SAR images to delineate ocean oil slicks with a texture-classifying neural network algorithm (TCNNA)

Satellite-borne synthetic aperture radar (SAR) data are widely used for detection of hydrocarbon resources, pollution, and oil spills. These applications require recognition of particular spatial patterns in SAR data. We developed a texture-classifying neural network algorithm (TCNNA), which processes SAR data from a wide selection of beam modes, to extract these patterns from SAR imagery in a semisupervised procedure. Our approach uses a combination of edge-detection filters, descriptors of texture, collection information (e.g., beam mode), and environmental data, which are processed with a neural network. Examples of pattern extraction for detecting natural oil seeps in the Gulf of Mexico are provided. The TCNNA was successful at extracting targets and rapidly interpreting images collected under a wide range of environmental conditions. The results allowed us to evaluate the effects of different environmental conditions on the expressions of oil slicks detected by the SAR data. By processing hundreds of SAR images, we have also found that the optimum wind speed range to study surfactant films is from 3.5 to 7.0 m·s–1, and the best incidence angle range for surfactant detection in C-band is from 22° to 40°. Minor postprocessing supervision is required to check TCNNA output. Interpreted images produce binary arrays with imbedded georeference data that are easily stored and manipulated in geographic information system (GIS) data layers.

A Multifrequency Polarimetric SAR Processing Chain to Observe Oil Fields in the Gulf of Mexico

Within the National Environmental Satellite, Data, and Information Service, National Oceanic and Atmospheric Administration, multiplatform synthetic aperture radar (SAR) imagery is being used to aid post hurricane and postaccident response efforts in the Gulf of Mexico, such as in the case of the recent Deepwater Horizon oil spill. The main areas of interest related to such disasters are the following: (1) to identify oil pipeline leaks and other oil spills at sea and (2) to detect man-made metallic targets over the sea. Within the context of disaster monitoring and response, an innovative processing chain is proposed to observe oil fields (i.e., oil spills and man-made metallic targets) using both Land C-band full-resolution and fully polarimetric SAR data. The processing chain consists of two steps. The first one, based on the standard deviation of the phase difference between the copolarized channels, allows oil monitoring. The second one, based on the different symmetry properties that characterize man made metallic targets and natural distributed ones, allows man made metallic target observation. Experiments, accomplished over single-look complex L-band Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) and C-band RADARSAT-2 fully polarimetric SAR data gathered in the Gulf of Mexico and related to the Deepwater Horizon accident, show the effectiveness of the proposed approach. Furthermore, the proposed approach, being able to process both Land C-band fully polarimetric and full resolution SAR measurements, can take full benefit of both the ALOS PALSAR and RADARSAT-2 missions, and therefore, it allows enhancing the revisit time and coverage which are very critical issues in oil field observation.

Comparison of Ocean Surface Winds From ENVISAT ASAR, MetOp ASCAT Scatterometer, Buoy Measurements, and NOGAPS Model

In this paper, we perform a comparison of wind speed measurements from the ENVISAT Advanced Synthetic Aperture Radar (ASAR), the MetOp-A Advanced Scatterometer (ASCAT), the U.S. National Data Buoy Centers moored buoys, and the U.S. Navy Operational Global Atmospheric Prediction System (NOGAPS) model. These comparisons were made in near U.S. coast regions over a 17-month period from March 2009 to July 2010. The ASAR wind speed retrieval agreed well with the scatterometer and model estimates, with mean differences ranging from -0.69 to 0.85 m/s and standard deviations between 1.16 and 1.77 m/s, depending upon the ASAR beam mode type. The results indicate that ASAR-derived ocean surface wind speeds are as accurate as the ASCAT and NOGAPS wind products. Comparisons between ASCAT winds and synthetic aperture radar (SAR) winds averaged at different spatial resolutions show very little change. This demonstrates that it is suitable that the scatterometer wind retrieval geophysical model function, i.e., CMOD5, is used for SAR wind retrieval. The impact of C-band VV polarization SAR calibration error on wind retrieval is also discussed.

Observation of hurricane-generated ocean swell refraction at the Gulf Stream north wall with the RADARSAT-1 synthetic aperture radar

We analyze the refraction of long oceanic waves at the Gulf Streams north wall off the Florida coast as observed in imagery obtained from the RADARSAT-1 synthetic aperture radar (SAR) during the passage of Hurricane Bonnie on August 25, 1998. The wave spectra are derived from RADARSAT-1 SAR images from both inside and outside the Gulf Stream. From the image spectra, we can determine both the long waves dominant wavelength and its propagation direction with 180/spl deg/ ambiguity. We find that the wavelength of hurricane-generated ocean waves can exceed 200 m. The calculated dominant wavelength from the SAR image spectra agree very well with in situ measurements made by National Oceanic and Atmospheric Administration National Data Buoy Center buoys. Since the waves mainly propagate toward the continental shelf from the open ocean, we can eliminate the wave propagation ambiguity. We also discuss the velocity-bunching mechanism. We find that in this very long wave case, the RADARSAT-1 SAR wave spectra should not be appreciably affected by the azimuth falloff, and we find that the ocean swell measurements can be considered reliable. We observe that the oceanic long waves change their propagation directions as they leave the Gulf Stream current. A wave-current interaction model is used to simulate the wave refraction at the Gulf Stream boundary. In addition, the wave shoaling effect is discussed. We find that wave refraction is the dominant mechanism at the Gulf Stream boundary for these very long ocean swells, while wave reflection is not a dominant factor. We extract 256-by-256 pixel full-resolution subimages from the SAR image on both sides of the Gulf Stream boundary, and then derive the wave spectra. The SAR-observed swell refraction angles at the Gulf Stream north wall agree reasonably well with those calculated by the wave-current interaction model.