Weather Analysis and Forecasting
Applying Satellite Water Vapor Imagery and Potential Vorticity Analysis

Presents the latest methods for analyzing and interpreting satellite data and images to improve understanding of atmospheric thermodynamics, including relevant operational forecasting methods to use data from numerical weather prediction models along with helpful illustrations based on real meteorological situations

Christo Georgiev (Author), Patrick Santurette (Author), Karine Maynard (Author)

9780128001943

Paperback, published 11 July 2016

360 pages, 340 illustrations (340 in full color)
23.4 x 19 x 2.3 cm, 0.75 kg

Weather Analysis and Forecasting: Applying Satellite Water Vapor Imagery and Potential Vorticity Analysis, Second Edition, is a step-by-step essential training manual for forecasters in meteorological services worldwide, and a valuable text for graduate students in atmospheric physics and satellite meteorology. In this practical guide, P. Santurette, C.G. Georgiev, and K. Maynard show how to interpret water vapor patterns in terms of dynamical processes in the atmosphere and their relation to diagnostics available from numerical weather prediction models. In particular, they concentrate on the close relationship between satellite imagery and the potential vorticity fields in the upper troposphere and lower stratosphere. These applications are illustrated with color images based on real meteorological situations over mid-latitudes, subtropical and tropical areas.

Part I: Fundamentals1. A dynamical view of synoptic development2. The interpretation problem of satellite water vapor imageryPart II: Practical use of water vapor imagery and thermodynamical fields3. Significant water vapor imagery features associated with synoptic thermodynamic structures4. Diagnosis of thermodynamic environment of deep convection5. Use of water vapor imagery to assess NWP model behavior and to improve weather forecastsAppendix A. Radiation measurements in water vapor absorption bandAppendix B. PV modification technique and PV inversion to correct the initial state of the numerical model

Subject Areas: Meteorology & climatology [RBP]