Satellite data can be very useful in applications where extensive spatial information is needed, but sometimes missing data due to presence of clouds can affect data quality. In this study a methodology for pre-processing sea surface temperature (SST) data is proposed. The methodology, that processes measures in the visible wavelength, is based on an Artificial Neural Network (ANN) system. The ...

[1] The Arctic is warming two to four times faster than the global average. Debate continues on the relative roles of local factors, such as sea ice reductions, versus remote factors in driving, or amplifying, Arctic warming. This study examines the vertical profile and seasonality of observed tropospheric warming, and addresses its causes using atmospheric general circulation model simulations...

This chapter reviews the progress made in the past decade in understanding tropical Atlantic climate variability. In addition to an equatorially anti-symmetric seasonal cycle forced directly by the seasonal march of the sun, Atlantic sea surface temperature (SST) displays a pronounced annual cycle on the equator that results from continental monsoon forcing and air-sea interaction. This cycle i...

The beginning of the 21st century was marked by a number of severe summer floods in Central Europe associated with extreme precipitation (e.g., Elbe 2002, Oder 2010 and Danube 2013). Extratropical storms, known as Vb-cyclones, cause summer extreme precipitation events over Central Europe and can thus lead to such floodings. Vb-cyclones develop over the Mediterranean Sea, which itself strongly w...

a r t i c l e i n f o Cross-evaluation of sea surface temperature (SST) algorithms was undertaken using split-window channels of Meteosat Second Generation Spinning Enhanced Visible and Infrared Imager (SEVIRI) as a proxy for the Geostationary Operational Environmental Satellites-R (GOES-R) Advanced Baseline Imager (ABI). The goal of the study was to select the algorithm which provides the high...

[1] The relationships among the boreal spring Southern Hemisphere Annular Mode (SAM), the Indian Ocean (IO) sea surface temperature (SST), and East Asian summer monsoon (EASM) are examined statistically in this paper. The variability of boreal spring SAM is closely related to the IO SST. When the SAM is in its strong positive phase in boreal spring, with low-pressure anomalies over the south po...

We examine processes that influence North Pacific sea surface temperature (SST) anomalies including surface heat fluxes, upper ocean mixing, thermocline variability, ocean currents, and tropical-extratropical interactions via the atmosphere and ocean. The ocean integrates rapidly varying atmospheric heat flux and wind forcing, and thus a stochastic model of the climate system, where white noise...

Operational multi-channel algorithms for deriving sea surface temperature (SST) from satellite data are derived using theoretical models of infrared radiation transfer through the atmosphere or by regression of satellite data with ground-based observations. In both cases the algorithm derivation implies a “first-guess” of the water vapour content along the atmospheric path between the satellite...

A nonlinear forecast system for the sea surface temperature (SST) anomalies over the whole tropical Pacific has been developed using a multi-layer perceptron neural network approach, where sea level pressure and SST anomalies were used as predictors to predict the five leading SST principal components at lead times from 3 to 15 months. Relative to the linear regression (LR) models, the nonlinea...