WRF Simulations to Investigate Processes Across Scales (WRFSCALE)

Hans-Stefan Bauer (), Thomas Schwitalla (), Oliver Branch (), Rohith Thundathil (), Stephan Adam () and Volker Wulfmeyer ()
Additional contact information
Hans-Stefan Bauer: Institute of Physics and Meteorology
Thomas Schwitalla: Institute of Physics and Meteorology
Oliver Branch: Institute of Physics and Meteorology
Rohith Thundathil: Institute of Physics and Meteorology
Stephan Adam: Institute of Physics and Meteorology
Volker Wulfmeyer: Institute of Physics and Meteorology

A chapter in High Performance Computing in Science and Engineering '19, 2021, pp 501-519 from Springer

Abstract: Abstract Several scientific aspects ranging from boundary layer research and land modification experiments to data assimilation applications were addressed with the Weather Research and Forecasting (WRF) model from the km-scale down to the turbulence-permitting scale. Case study simulations in as different regions as the central United States, the United Arab Emirates and southwestern Germany were performed to investigate the evolution of the convective boundary layer. The multi-nested WRF setup, driven by the operational analysis of the European Centre for Medium-range Weather Forecasts (ECMWF), high-resolution terrain, and land cover data sets simulated a realistic evolution of the internal turbulent structure of the boundary layer including the transitions between daytime and nighttime conditions. Land modification simulations in the United Arab Emirates demonstrated that plantations as small as 10 $$\,\times \,$$ × 10 km $$^2$$ 2 could modify the weather pattern in this area in a way that more precipitation reaches the desert. Data assimilation experiments demonstrated the beneficial influence of state-of-the-art lidar measurements on the forecast performance of WRF. A further improvement was found when the more sophisticated hybrid 3DVAR-ETKF method was applied, since this method includes a flow-dependent model error contribution and thus more realistically spreading the information of the observations.

Date: 2021
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-66792-4_34

Ordering information: This item can be ordered from
http://www.springer.com/9783030667924

DOI: 10.1007/978-3-030-66792-4_34

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().