Assimilation of satellite data for global numerical weather prediction

Computer Science – Sound

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

The object of assimilation for NWP is to find an internally consistent model state which best fits all available information. This comes from remote sensing and in situ observations for the present time and the past few days; the NWP model is essential for the efficient use of earlier data. The determination of ``best fit'' must take account of the error characteristics of observations and model; Gaussian errors and a linearizable model give idealized equation with convenient properties, but gross errors and biases in observations are important, and spoil these. The growing diversity and volume of satellite data makes some pre-processing, before incorporation in NWP assimilations, essential. However it is important that the processing and assimilation is conceived as a single integrated process.
The paper gives a brief summary of the theory, and approximate implementation, of the ideal equations, and how non-Gaussian errors affect this. Examples are considered from satellite temperature soundings, wind lidar, and radar scatterometer winds.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Assimilation of satellite data for global numerical weather prediction does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Assimilation of satellite data for global numerical weather prediction, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Assimilation of satellite data for global numerical weather prediction will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-1203527

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.