Advances in Satellite Sea Surface Temperature Measurement and Oceanographic Applications

نویسنده

  • R. M.
چکیده

Satellite techniques for measurement of sea surface temperature (SST) are reviewed briefly, and a discussion of satellite SST applications and recent research in oceanography is provided. These applications include the areas of climate, mesoscale oceanography, and fisheries. Examples given focus mainly on the Pacific and California Current regions. Satellite SST data are currently used operationally for fisheries applications and, in conjunction with in situ data, are providing new insights into mesoscale oceanographic phenomena. Requirements for sensor precision and calibration accuracy are more stringent in air-sea interaction studies and climate research, thus satellite data have gained only qualified acceptance for these applications. Improvements in future satellite instruments, more comprehensive in situ sensor deployments, and better data management procedures should eventually satisfy most oceanography and climate SST requirements.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

تحلیل حرکت جریانات دریائی در تصاویر حرارتی سطح آب دریا

Oceanographic images obtained from environmental satellites by a wide range of sensors allow characterizing natural phenomena through different physical measurements. For instance Sea Surface Temperature (SST) images, altimetry data and ocean color data can be used for characterizing currents and vortex structures in the ocean. The purpose of this thesis is to derive a relatively complete frame...

متن کامل

The pattern determination of sea surface temperature distribution and chlorophyll a in the Southern Caspian Sea using SOM Model

Remote sensing has changed modern oceanography by proving synoptic periodic data which can be processed. Since the satellite data are usually too much and nonlinear, in most cases, it is difficult to distinguish the patterns from these images. In fact, SOM (Self-Organizing Maps) model is a type of ANN (Artificial Neural Network) that has the ability to distinguish the efficient patterns from th...

متن کامل

The pattern determination of sea surface temperature distribution and chlorophyll a in the Southern Caspian Sea using SOM Model

Remote sensing has changed modern oceanography by proving synoptic periodic data which can be processed. Since the satellite data are usually too much and nonlinear, in most cases, it is difficult to distinguish the patterns from these images. In fact, SOM (Self-Organizing Maps) model is a type of ANN (Artificial Neural Network) that has the ability to distinguish the efficient patterns from th...

متن کامل

Investigation of Geostrophic and Ekman Surface Current Using Satellite Altimetry Observations and Surface Wind in Persian Gulf and Oman Sea

The rise of satellite altimetry is a revolution in the ocean sciences. Due to its global coverage and its high resolution, altimetry classically outperforms in situ water level measurement. Ekman and geostrophic currents are large parts of the ocean’s current, playing a vital role in global climate variations. According to the classic oceanography, Ekman and geostrophic currents can be calculat...

متن کامل

Linear Gaussian State-Space Model with Irregular Sampling - Application to Sea Surface Temperature

Satellites provide important information on many meteorological and oceanographic variables. State-space models are commonly used to analyse such data sets with measurement errors. In this work, we propose to extend the usual linear and Gaussian state-space to analyse time series with irregular time sampling, such as the one obtained when keeping all the satellite observations available at some...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2004