MARC Record from Library of Congress

LEADER: 03079cam a2200277 a 4500
001 2010035492
003 DLC
005 20110926134736.0
008 100818s2011 enka b 001 0 eng
010 $a 2010035492
020 $a9780521513890 (hbk.)
040 $aDLC$cDLC$dDLC
042 $apcc
050 00 $aQC996$b.W37 2011
082 00 $a551.63/4$222
100 1 $aWarner, Thomas T.
245 10 $aNumerical weather and climate prediction /$cThomas Tomkins Warner.
260 $aCambridge ;$aNew York :$bCambridge University Press,$c2011.
300 $axxii, 526 p. :$bill. ;$c26 cm.
520 $a"This textbook provides a comprehensive yet accessible treatment of weather and climate prediction, for graduate students, researchers, and professionals. It teaches the strengths, weaknesses, and best practices for the use of atmospheric models. It is ideal for the many scientists who use such models across a wide variety of applications. The book describes the different numerical methods, data assimilation, ensemble methods, predictability, land surface modeling, climate modeling and downscaling, computational fluid-dynamics models, experimental designs in model-based research, verification methods, operational prediction, and special applications such as air-quality modeling and flood prediction. The book is based on a course that the author has taught for over 30 years at the Pennsylvania State University and the University of Colorado at Boulder, and also benefits from his wide practical modeling experience at the US National Center for Atmospheric Research. This volume will satisfy everyone who needs to know about atmospheric modeling for use in research or operations. It is ideal both as a textbook for a course on weather and climate prediction and as a reference text for researchers and professionals from a range of backgrounds: atmospheric science, meteorology, climatology, environmental science, geography, and geophysical fluid mechanics/dynamics"--$cProvided by publisher.
504 $aIncludes bibliographical references (p. 461-522) and index.
505 8 $aMachine generated contents note: Preface; List of acronyms; List of symbols; 1. Introduction; 2. The governing systems of equations; 3. Numerical solutions to the equations; 4. Physical-process parameterizations; 5. Modeling surface processes; 6. Model initialization; 7. Ensemble methods; 8. Predictability; 9. Verification methods; 10. Experimental design in model-based research; 11. Techniques for analyzing model output; 12. Operational numerical weather prediction; 13. Statistical post processing of model output; 14. Coupled special-applications models; 15. Computational fluid-dynamics models; 16. Climate modeling and downscaling; Appendix A. Suggested code structure and experiments for a simple shallow-fluid model; References; Index.
650 0 $aNumerical weather forecasting.
650 0 $aWeather forecasting$xMathematical models.
650 0 $aClimatology$xMathematical models.
856 42 $3Cover image$uhttp://assets.cambridge.org/97805215/13890/cover/9780521513890.jpg