Pablo Clemente-Colón

Rapid reduction of Arctic perennial sea ice

[1] The extent of Arctic perennial sea ice, the year-round ice cover, was significantly reduced between March 2005 and March 2007 by 1.08 x 10 6 km 2 , a 23% loss from 4.69 × 10 6 km 2 to 3.61 × 10 6 km 2 , as observed by the QuikSCAT/SeaWinds satellite scatterometer (QSCAT). Moreover, the buoy-based Drift-Age Model (DM) provided long-term trends in Arctic sea-ice age since the 1950s. Perennial-ice extent loss in March within the DM domain was noticeable after the 1960s, and the loss became more rapid in the 2000s when QSCAT observations were available to verify the model results. QSCAT data also revealed mechanisms contributing to the perennial-ice extent loss: ice compression toward the western Arctic, ice loading into the Transpolar Drift (TD) together with an acceleration of the TD carrying excessive ice out of Fram Strait, and ice export to Baffin Bay. Dynamic and thermodynamic effects appear to be combining to expedite the loss of perennial sea ice.

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.

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

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.

A two-scale model to predict C-band VV and HH normalized radar cross section values over the ocean

This paper presents a two-scale model that can predict C-band, VV polarized (C-VV), normalized radar cross section values generated from the CMOD4 model and calibrated normalized radar cross section values derived from C-band, HH polarized (C-HH), RADARSAT-1 synthetic aperture radar imagery with coincident buoy observations of the local wind. The model is based on standard composite models that incorporate tilt modulations, with a new approach for incorporating hydrodynamic modulations. It is shown that inclusion of the hydrodynamic term does not significantly impact the fit to normalized radar cross section (NRCS) values, but does allow the model to accurately predict the upwind to downwind C-VV ratios and improves the model fit to simultaneous C-VV and C-HH NRCS observations. The model uses a new wave height spectrum that is a linear combination of the Apel and Romeiser spectra, weighted heavily toward the Apel form, and has modified values within the C-band Bragg wavenumber regime which are close to midway between the two spectra. The final model can represent the CMOD4 C-VV NRCS results with a root-mean-square error (RMSE) of 0.47 dB and can represent the RADARSAT-1 C-HH NRCS observations, without any change to the model parameters, with an RMSE of 1.9 dB. The model can accurately reproduce the upwind to downwind C-VV NRCS ratios from CMOD4 (RMSE = 0.15 dB) and fits simultaneous C-VV to C-HH ratios derived from aircraft observations to within 1 dB (RMSE = 0.65 dB). If the C-HH hydrodynamic term is allowed to be scaled differently than the C-VV hydrodynamic term, it lowers the RMSE for the simultaneous C-VV to C-HH aircraft observations to 0.49 dB while not affecting the fit to C-VV and C-HH NRCS values. Compared to other C-HH models published in the literature, this model provides a better fit to the RADARSAT-1 C-HH NRCS data across a larger range of conditions than any other single model, provides a better fit to simultaneous C-VV and C-HH NRCS data at an incidence angle of 20°, and reproduces the decreasing trend in the C-VV to C-HH ratio with increasing wind speed observed in data.

Atmospheric vortex streets on a RADARSAT SAR image

We analyze the sea surface imprint of two atmospheric vortex streets (AVSs) observed on a RADARSAT, a Canadian earth observation satellite, Synthetic Aperture Radar (SAR) image of the Aleutian Islands in the western Gulf of Alaska acquired on May 5, 1999. The RADARSAT SAR instrument is operated in C-band with HH polarization. These AVSs are interpreted as the atmosphere analog of classic Von Karman vortex streets. The SAR image, along with radiosonde data and surface weather charts, reveal that the AVS lengths are 196 km and 111 km for AVS-1 and AVS-2, respectively. There are five and two pairs of vortices within each AVS. The vortex shedding period is estimated to be between 35 and 48 minutes. The vortex shedding started approximately 4.6 and 2.6 hours prior to the SAR imaging time for AVS-1 and AVS-2, respectively. There are seven and three pairs of vortices within the respective AVSs. The vortex tangential velocity is estimated to be between 1.7 and 2.3 m/s and the energy dissipated during the vortex lifetime is estimated to be between 24.9 and 23.6 J/m³.

Deriving the operational nonlinear multichannel sea surface temperature algorithm coefficients for NOAA-15 AVHRR/3

The National Oceanic and Atmospheric Administration (NOAA) currently uses Nonlinear Sea Surface Temperature (NLSST) algorithms to estimate sea surface temperature (SST) from NOAA satellite Advanced Very High Resolution Radiometer (AVHRR) data. In this study, we created a three-month dataset of global sea surface temperature derived from NOAA-15 AVHRR data paired with coincident SST measurements from buoys (i.e. called the SST matchup dataset) between October and December 1998. The satellite sensor SST and buoy SST pairs were included in the dataset if they were coincident within 25 km and 4 hours. A regression analysis of the data in this matchup dataset was used to derive the coefficients for the operational NLSST equations applicable to NOAA-15 AVHRR sensor data. An independent matchup dataset (between January and March 1999) was also used to assess the accuracy of these day and night operational NLSST algorithms. The bias was found to be 0.14°C and 0.08°C for the day and night algorithms, respectively. The standard deviation was 0.5°C or less.

Observations of East Coast upwelling conditions in synthetic aperture radar imagery

Seasonal coastal upwelling in the U.S. Mid-Atlantic coastal ocean normally occurs during the summer months because of generally alongshore southerly wind episodes. Southerly winds force an offshore surface Ekman flow over the inner continental shelf. Colder and nutrient-rich waters from below upwell toward the surface replacing offshore-flowing surface waters. Synthetic Aperture Radar (SAR) observations from the European Remote Sensing (ERS) satellite ERS-2 before and after upwelling-favorable wind episodes in early summer 1996 along the New Jersey coast are presented. Lower backscatter conditions appearing in the SAR imagery after the onset of upwelling demonstrate the influence of the upwelling regime on the sea surface roughness. Satellite sea surface temperature (SST) observations and in-situ sea temperature vertical profiles confirm upwelling conditions. Three key mechanisms are suggested to explain the lower radar returns observed under upwelling conditions, an increase in the atmospheric marine boundary layer stability, an increase in the viscosity of surface waters, and the presence of biogenic surfactants in the upwelling region.

Measuring Trans‐Atlantic aerosol transport from Africa

An estimated three billion metric tons of mineral aerosols are injected into the troposphere annually from the Saharan desert [Prospero et al., 1996]. Additionally, smoke from biomass burning sites in the savanna grasslands in sub-Saharan Africa contribute significant quantities of smaller-sized aerosols [e.g., Hobbs, 2000]. These windswept aerosols from the African continent are responsible for a variety of climate, health, and environmental impacts on both global and regional scales that span the Western Hemisphere. Unfortunately in situ measurements of aerosol evolution and transport across the Atlantic are difficult to obtain, and satellite remote sensing of aerosols can be challenging.