Upwelling is an oceanographic process that transfers cool and nutrient-rich waters toward the sea surface. Due to the relation between low sea surface temperature (SST) and high nutrient-rich water, the upwelling regions can be easily recognized in satellite imagery. An optical flow (OF) method, Horn–Schunck, is used to discover the upwelled water motion (UWM) and its pattern using sequential (pair) SST imageries. The SST imageries of Aqua and Terra satellites between 2004 and 2012 are processed to extract the properties of upwelling in the Shevchenko area (Caspian Sea). Results show that the upwelling is periodic (with an ∼24 h period) and it matches with a Fourier model. In addition, the UWM has a specific direction from morning to night. It is also shown that the OF cannot extract correct UWM if the SST imageries are selected on different cycles. Level of chlorophyll_a in the same area is used to independently validate the existence of the upwelling.
Satellite altimetry has proven to be a useful tool to study oceanic processes in the deep ocean; however, its use is still limited in shallow waters near the coast where two main issues still need a more detailed analysis. On one side, the local characteristics of each coastal region imply that certain corrections applied to the altimetry measurements need to be reanalysed. On the other side, the radar signal retracking algorithms need to be improved because the waveforms do not follow the Brown's model, which is designed for deep waters. The ESA mission Envisat was launched in March 2002 with a dual-frequency radar altimetry (RA-2). The satellite was operative until the end of the mission in May 2012. The ESA mission Cryosat-2 was launched in April 2010 being still in operation. The radar instrument on-board Cryosat-2 improves the capabilities of previous pulse-limited altimeters, such as Envisat RA-2. The Spanish-funded ALCOVA project aims at analyzing and improving the altimetry measurements obtained from these two altimetry missions. Regarding the RA-2 data a new prototype retracker -ALES- has been developed under the frame of the ESA-DUE eSurge project. Two pilot regions are proposed, namely, the Gulf of Cadiz and the Strait of Gibraltar in the Southwestern Iberian Peninsula. Cryosat-2 data (in SAR mode), the newly corrected RA-2 data (based on ALES) and the standard RA- 2 product (based on Brown's model) are being validated with available in-situ data (sea level height) to ensure their correct performance in the selected coastal areas.
Satellite altimetry has proved successful as a global tool for monitoring sea surface height, significant wave height and
wind speed. Nevertheless, a global archive of 17 years of raw data from a series of missions is presently unexploited
around the world coastline. This huge amount of unused data can be re-analyzed, improved and more intelligently
exploited, possibly promoting coastal altimetry to the rank of operational service. Operational users interested in
monitoring sea level change and wave conditions in the coastal zone (e.g. for coastal erosion, sediment/pollutant
transport applications) still rely on sparse (and expensive) in situ monitoring stations or poor models. In this work we
present a new approach in the exploitation of altimeter data in the coastal zone (currently impeded by unsuitable
waveform retracking scheme and coarse along-track spatial sampling in the coastal zone, among others). The objective
of this paper is to show how a new, robust, retracking algorithm is able to retrieve with high accuracy physical ocean
parameters from altimeter waveforms in the coastal zone. The main focus lies on retrieving sea surface height in the
coastal zone with the same precision as is achieved in the open ocean. In addition, the retrieval of more accurate
altimeter-derived wave products in the coastal zone is also important as waves are more directly relevant to many
operational applications in the coastal zone.
Fifteen years of global altimetry data over the coastal ocean lie, largely unexploited, in the data archives, simply because
intrinsic difficulties in the corrections and issues of land contamination in the footprint. These data would be invaluable
for studies of coastal circulation, sea level change and impact on the coastline. Amongst some initiatives, we describe
here the COASTALT Project, funded by ESA. The main objective of the COASTALT Project is to contribute towards
making the status of pulse-limited coastal altimetry operational. In this paper we will first illustrate the first project
phase, based on the assessment of user requirements, and summarize those requirements. Then we will describe the
COASTALT methodology and objectives. Finally, we will illustrate and discuss the various options for coastal
waveform retracking, and present a plan for the validation of the retracked data. The first results in the radar altimeter
waveform analysis show the complexity of the coastal signals due to land contamination and calm/rough waters.
The history of satellite radar altimetry stems from the need to capture a global view of the surface topography of the oceans. As altimeters are specifically designed for global observations, they encounter major problems in coastal regions, such as relatively poor sampling and inaccuracy of the corrections, so measurements are generally discarded. Nevertheless, a global archive of 15 years of raw data from a series of missions is presently available. The huge amount of unused data in coastal regions can be re-analyzed, improved and more intelligently exploited, possibly promoting coastal altimetry to the rank of operational service. This paper outlines the obstacles limiting the use of the data, discusses some areas of improvement, shows the lessons learned from a case-study in the Mediterranean Sea, and shows that the improved coastal altimetry concept can be extended to other regions, e.g. along the coasts of India. This paper also explores the implications of adopting the emerging vision of the Internet infrastructure in the coastal altimetry context: a collection of unstructured information becomes a network of linked data and software, necessary to perform the specialized on-the-fly processing of the raw data to provide ready-to-use geophysical parameters such as sea level and significant wave height.