Surprising new ozone data from NASA satellite

New NASA satellite - to - satellite communications take shape

Neural Network Algorithms for Tropospheric Ozone Retrieval from Esa-envisat Sciamachy and Nasa-aura Omi Satellite Data

The ozone in troposphere is a direct greenhouse gas [1] and its importance, both from a radiative point of view and concerning its interaction with the biosphere, is outlined in several scientific papers. Monitoring its trends, especially in highly polluted locations, is a relevant topic in recent geo-sciences research. Obtaining information about ozone in the lower atmospheric levels from spac...

On the assimilation of total-ozone satellite data

A two-dimensional model for advection and data assimilation of total-ozone data has been developed. The Assimilation Model KNMI (AMK) is a global model describing the transport of the column amounts of ozone, by a wind field at a single pressure level, assuming that total ozone behaves as a passive tracer. In this study, ozone column amounts measured by the TIROS Operational Vertical Sounder (T...

Grid Technology and Neural Networks for the Analysis of Atmospheric Ozone from Satellite Data

The problem of the retrieval of spatial ozone distribution from radiance measurements collected by the GOME (Global Ozone Monitoring Experiment) instrument on board of ERS-2 satellite is addressed. We propose a neural network approach for the implementation of the inversion method in a Grid technology environment

Ozone Distributions Derived from Satellite Data Assimilation and Their Impact on the Stratospheric Temperatures

Using a linear version of the ECMWF radiative transfer code it is possible to evaluate the impact of a prescribed ozone climatology on the stratospheric temperatures produced by climate models. So far referenced ozone climatologies have been derived by compilations and simple spatial interpolations of satellite and soundings data with rather coarse vertical resolutions and sometimes inhomogeneo...