Angular dependence of wind-driven sea-surface retroreflectance
Concurrent measurements of sea-surface retroreflectance and associated wind velocity provide insight into thermal-infrared optical phenomenology of air-sea interface processes.
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Concurrent measurements of sea-surface retroreflectance and associated wind velocity provide insight into thermal-infrared optical phenomenology of air-sea interface processes.
Sea Surface Temperatures (SST) as derived from the Pathfinder Sea Surface Temperature Data Set and the Along-Track Scanning Radiometer on-board the European Remote Sensing Satellite provide a unique opportunity for comparing two independent SST data sets.
This study aims to identify the controlling processes of phytoplankton distributions in the Alboran Sea (western Mediterranean Sea).
Large cyclonic and anticyclonic eddies are found in the Caribbean Sea. Analysis of sea level data from the TOPEX/Poseidon altimeter shows that the eddies are quite regular,......
The dependence of sea surface directional reflectance on surface wind speed from space-based lidar measurements of sea surface backscatter. In particular lidar measurements in the nidir angle range from 10-30 degrees appear to be most sensitive to surface wind speed variability in the regime below 10m/s.
Since 1991 a suite of international satellites have collected large amounts of high-resolution microwave radar images over Arctic and Antarctic sea ice. Together with complementary synthetic aperture radar (SAR) 100 m resolution microwave imaging, these data provide a powerful tool for addressing the characteristics of sea ice which directly influence the polar oceans and climate.
Changes in sea ice conditions have major effects on the ocean and on weather, but visual observations miss periods of cloudiness and darkness. Microwave radar satellites are the only uninterrupted source of high resolution (30 m) data. Recent developments will allow high-resolution global sea-ice tracking at intervals of a few days.
The sea surface temperature over the Arabian Sea during the 1987-1993 monsoons will be described from Advanced Very High Resolution Radiometer measurements recorded on the National Oceanic and Atmospheric Administration polar-orbiting spacecrafts.
Physical, structural, and electromagnetic properties and interrelating processes in sea ice are used to develop a composite model for polarimetric backscattering signatures of sea ice.
Experimental observations of sea ice polarimetric signatures in the Beaufort Sea under cold winter conditions are presented and interpreted with the composite model developed in Part I.
The sea state bias in altimeter measurements of sea surface height has been investigated by many authors, resulting in several proposed algorithms of the form SSB = epsilonH where H is the significant wave height and epsilon is a nondimensional function of wind and wave parameters. All known algorithms are presently rated. By analyzing the performance of different models we conclude that further progress can hardly be achieved by raising the degree of the polynomial for epsilon(U,H). Physically based approaches employing a small number of adjustable parameters and theoretically justified non-dimensional combinations of external wind and wave factors appear to be more promising.
This research examines the seasonal changes of the sea ice cover in the Arctic Basin as it responds to atmospheric and oceanic conditions. Monitoring this process provides a means of determining the onset and extent of the annual seasonal stages, which is thought to be an indicator for detecting climate change in the polar regions. Much of the response of sea ice to seasonal conditions results in changes in the phase of water (both in the ice and snow cover), surface roughness, and internal properties such as air bubbles. Imagery from SAR has proven to be an important tool for revealing these changes since radar backscatter is affected by both surface roughness and dielectric properties of water and salt. The major ice types and ice features may have unique SAR backscatter signatures because of the inherent variations in surface roughness, salinity, and internal properties in each category.
Investigations of the sea state bias in TOPEX altimeter measurements of sea surface height show considerable regional variability of the estimated SSB values.
This paper presents results from a study of multiple-polarization C-band SAR signitures of sea ice for applications to sea ice mapping with ENVISAT ASAR data.
The circulation and upwelling processes (coastal and gyre-induced) that control the phytoplankton distribution in the Alboran sea are examined by analyzing monthly climatological patterns of Coastal Zone Color Scanner (CZCS) pigment concentrations, sea surface temperatures, winds, and seasonal geostrophic fields.
In this paper, we provide a short review of sea ice investigations starting from Seasat. We focus particularly on the detailed and quantitative measurements of the sea ice motion field, which were some of the earliest results from Seasat and have sugsequently been shown to be of critical value to the derivation of several key climatically important variables. Other key investigations discussed include examination of the seasonal melt cycle, ice extent and concentration, and estimates of thickness from the proxy measurements of ice type and age and more directly from freeboard. We end with a brief discussion on how thse measurements might be improved in the future.
Four years (1997-2000) of RADARSAT Geophysical Processor System (RGPS) data are used to contrast the sea ice deformation and production regionally, and in the seasonal (SIZ) and perennial (PIZ) ice zones. Ice production is of seasonal ice in openings during the winter. Three-day estimates of these quantities are provided within Lagrangian elements initially 10 km on a side. A distinct seasonal cycle is seen in both zones with these estimates highest in the late fall and with seasonal minimums in the midwinter. Regional divergence over the winter could be up to 30%. Spatially, the highest deformation is seen in the SIZ north of coastal Alaska. Both ice deformation and production are higher in the SIZ: deformation-related ice production in the SIZ (approx.0.5 m) is 1.5-2.3 times that of the PIZ (approx.0.3 m): this is connected to ice strength and thickness. Atmospheric forcing and boundary layer structure contribute to only the seasonal and interannual variability. Seasonal ice growth in ice fractures accounts for approx.25-40% of the total ice production of the Arctic Ocean. Uncertainties in these estimates are discussed. By itself, this deformation-ice production relationship could be considered a negative feedback when thickness is perturbed. However, the overall effect on ice production in the face of increasing seasonal and thinner/weaker ice coverage could be modified by local destabilization of the water column promoting overturning of warmer water due to increased brine rejection; and the upwelling of the pynocline associated with increased occurrence of large shear motion in sea ice. Divergence is shown to be negligibly correlated to cyclonic motion in summer and winter in both ice zones.
The presentation includes an introduction, Lake Tahoe site layout and measurements, Salton Sea site layout and measurements, field instrument calibration and cross-calculations, data reduction methodology and error budgets, and example results for MODIS. Summary and conclusions are: 1) Lake Tahoe CA/NV automated validation site was established in 1999 to assess radiometric accuracy of satellite and airborne mid and thermal infrared data and products. Water surface temperatures range from 4-25C.2) Salton Sea CA automated validation site was established in 2008 to broaden range of available water surface temperatures and atmospheric water vapor test cases. Water surface temperatures range from 15-35C. 3) Sites provide all information necessary for validation every 2 mins (bulk temperature, skin temperature, air temperature, wind speed, wind direction, net radiation, relative humidity). 4) Sites have been used to validate mid and thermal infrared data and products from: ASTER, AATSR, ATSR2, MODIS-Terra, MODIS-Aqua, Landsat 5, Landsat 7, MTI, TES, MASTER, MAS. 5) Approximately 10 years of data available to help validate AVHRR.