Abstract
Although a terrain-following vertical coordinate is well suited for the application of surface boundary conditions, it iswell known that the influences of the terrain on the coordinate surfaces can contribute to increase numerical errors, particularly over steep topography. To reduce these errors, a hybrid sigma-pressure coordinate is formulated in the Weather Research and Forecasting (WRF) Model, and its effects are illustrated for both an idealized test case and a real-data forecast for upper-level turbulence. The idealized test case confirms that with the basic sigma coordinate, significant upper-level disturbances can be produced due to numerical errors that arise as the advection of strong horizontal flow is computed along coordinate surfaces that are perturbed by smaller-scale terrain influences. With the hybrid coordinate, this artificial noise is largely eliminated as the mid- and upper-level coordinate surfaces correspond much more closely to constant pressure surfaces. In real-data simulations for upper-level turbulence forecasting, theWRF Model using the basic sigma coordinate tends to overpredict the strength of upper-air turbulence over mountainous regions because of numerical errors arising as a strong upper-level jet is advected along irregular coordinate surfaces.With the hybrid coordinate, these errors are reduced, resulting in an improved forecast of upper-level turbulence. Analysis of kinetic energy spectra for these simulations confirms that artificial amplitudes in the smaller scales at upper levels that arise with the basic sigma coordinate are effectively removed when the hybrid coordinate is used.
Original language | English |
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Pages (from-to) | 971-985 |
Number of pages | 15 |
Journal | Monthly Weather Review |
Volume | 147 |
Issue number | 3 |
DOIs | |
Publication status | Published - 2019 Mar 1 |
Bibliographical note
Funding Information:Acknowledgments. (SHP) This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST; 2018R1A2B6008078) and (in part) by the Yonsei University Future-leading Research Initiative of 2018-22-0021. (JBK) Funding for the NCAR portion of this research was provided through support from the National Science Foundation under Cooperative Support Agreement AGS-0856145 and from the NOAA NCAR IDIQ T0006, distributed through the Developmental Testbed Center. NCAR is sponsored by the National Science Foundation.
Funding Information:
(SHP) This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST; 2018R1A2B6008078) and (in part) by the Yonsei University Future-leading Research Initiative of 2018-22-0021. (JBK) Funding for the NCAR portion of this research was provided through support fromthe National Science Foundation under Cooperative Support Agreement AGS-0856145 and from the NOAA NCAR IDIQ T0006, distributed through the Developmental Testbed Center. NCAR is sponsored by the National Science Foundation.
Publisher Copyright:
© 2019 American Meteorological Society.
All Science Journal Classification (ASJC) codes
- Atmospheric Science