Muutke küpsiste eelistusi

Uncertainties in Numerical Weather Prediction [Pehme köide]

4.00/5 (2 hinnangut Goodreads-ist)
Edited by (Research Meteorologist, Physical Sciences Laboratory, NOAA), Edited by (Professor, Reykjavik School of Meteorology, University of Iceland)
  • Formaat: Paperback / softback, 364 pages, kõrgus x laius: 235x191 mm, kaal: 760 g
  • Ilmumisaeg: 25-Nov-2020
  • Kirjastus: Elsevier Science Publishing Co Inc
  • ISBN-10: 0128154918
  • ISBN-13: 9780128154915
Teised raamatud teemal:
Uncertainties in Numerical Weather PredictionSuurem pilt
  • Formaat: Paperback / softback, 364 pages, kõrgus x laius: 235x191 mm, kaal: 760 g
  • Ilmumisaeg: 25-Nov-2020
  • Kirjastus: Elsevier Science Publishing Co Inc
  • ISBN-10: 0128154918
  • ISBN-13: 9780128154915
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780128154915.html
Märksõnad:

Uncertainties in Numerical Weather Prediction is a comprehensive work on the most current understandings of uncertainties and predictability in numerical simulations of the atmosphere. It provides general knowledge on all aspects of uncertainties in the weather prediction models in a single, easy to use reference. The book illustrates particular uncertainties in observations and data assimilation, as well as the errors associated with numerical integration methods. Stochastic methods in parameterization of subgrid processes are also assessed, as are uncertainties associated with surface-atmosphere exchange, orographic flows and processes in the atmospheric boundary layer.

Through a better understanding of the uncertainties to watch for, readers will be able to produce more precise and accurate forecasts. This is an essential work for anyone who wants to improve the accuracy of weather and climate forecasting and interested parties developing tools to enhance the quality of such forecasts.

  • Provides a comprehensive overview of the state of numerical weather prediction at spatial scales, from hundreds of meters, to thousands of kilometers
  • Focuses on short-term 1-15 day atmospheric predictions, with some coverage appropriate for longer-term forecasts
  • Includes references to climate prediction models to allow applications of these techniques for climate simulations

1. DYNAMICAL CORES FOR NWP: AN UNCERTAIN LANDSCAPE

2. DYNAMICAL MODEL DISCRETIZETION

3. PROBABILISTIC VIEW OF NUMERICAL WEATHER PREDICTION AND ENSEMBLE PREDICTION

4. PREDICTABILITY

5. MODELING MOIST DYNAMICS ON SUBGRID SCALES

6. ENSEMBLE DATA ASSIMILATION

7. SUBGRID TURBULENCE MIXING

8. UNCERTAINTIES IN THE SURFACE LAYER PHYSICS PARAMETERIZATIONS

9. INTERACTION OF CLOUDS AND RADIATION

10. UNCERTAINTIES IN THE PARAMETERIZATION OF CLOUD MICROPHYSICS: AN ILLUSTRATION OF THE PROBLEM

11. MEOSCALE OROGRAPHIC FLOWS

12. TRACERS AND ATMOSPHERIC RIVERS

13. DYNAMIC IDENTIFICATION AND TRACING OF ERRORS IN NUMERICAL SIMULATIONS OF THE ATMOSPHERE

Haraldur Ólafsson is a professor of atmospheric physics at the University of Iceland, leading the Reykjavik School of Meteorology. He is a former professor and the leader of the Bergen School of Meteorology at the University of Bergen in Norway. He has a doctorate from Université Paul Sabatier in France and a Cand. Scient. from the University of Oslo, Norway. Haraldur Olafsson is an expert in mesoscale meteorology and climatology and orographic processes. Jian-Wen Bao is a research meteorologist at NOAA Physical Sciences Laboratory. He was responsible for developing and testing the physics component of a research global weather prediction model. He is currently participating in a project as a project co-lead to develop an advanced physics suite in NOAAs Unified Forecast System.