Small-scale orographic gravity wave drag in stable boundary layers and its impact on synoptic systems and near surface meteorology

Aristofanis Tsiringakis, G.J. Steeneveld*, A.A.M. Holtslag

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

15 Citations (Scopus)

Abstract

At present atmospheric models for weather and climate use enhanced turbulent drag under stable conditions, because these empirically provide the necessary momentum drag for accurate forecast of synoptic systems. The enhanced mixing (also known as the "long-tail"), introduces drag that can not be physically justified and deteriorates the score for near surface temperature, wind and boundary-layer height, and deteriorates fog and frost forecasting. This study hypothesises that the insufficient representation of small-scale orographic gravity wave drag in the stable boundary layer may explain the need for the enhanced drag formulation. Hence, we introduce a new scheme in the WRF model that accounts for this drag as a superposition on the turbulent drag induced by a so-called short-tail mixing function. The latter is consistent with boundary-layer observations and large eddy simulations. We evaluate this scheme, against a short-tail and a long-tail scheme for sixteen 8-day forecasts over the Atlantic Ocean and Europe in winter. The new scheme outperforms the short and long tail schemes on sea level pressure, height of the 500 hPa field, 10 m wind and the cyclonic core pressure. Cyclonic core pressure bias is reduced by approximately 45% to 80% compared to the short-tail scheme. Sea level pressure bias is reduced by up to 0.48 hPa (50%) over the whole domain compared to the short-tail run. The new scheme has even smaller biases than the long-tail scheme, supporting our hypothesis that small-scale gravity wave drag may explain the need for a long-tail function. Near surface wind bias is reduced by up to 40% compared to the long-tail and up to 32% compared to the short-tail scheme, while the 2 m temperature bias is only slightly increased (19%).
Original languageEnglish
Pages (from-to)1504-1516
JournalQuarterly Journal of the Royal Meteorological Society
Volume143
Issue number704 Part A
DOIs
Publication statusPublished - 2017

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