Offline estimates and tuning of mesospheric gravity‐wave forcing using Met Office analyses

• Published in: Quarterly journal of the Royal Meteorological Society Vol. 140; no. 680; pp. 1025 - 1038
• Main Authors: Long, D. J., Jackson, D. R., Thuburn, J.
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 01.04.2014; Wiley; Wiley Subscription Services, Inc
• Subjects: Climatology; Earth, ocean, space; Estimates; Evolution; Exact sciences and technology; External geophysics; gravity‐wave forcing; Mathematical models; Mesosphere; Meteorology; Offices; Physics of the high neutral atmosphere; Spectra; Tuning; USSP scheme; Wind; gravity-wave forcing; Forcing; Mesosphere; Gravity wave; USSP scheme
• ISSN: 0035-9009; 1477-870X
• DOI: 10.1002/qj.2168

Estimates of small‐scale non‐orographic gravity‐wave forcing in the mesosphere are investigated using Met Office middle atmospheric analyses. Such estimates are obtained using the ultrasimple spectral parametrization (USSP) gravity‐wave scheme, currently employed operationally by the Met Office. A climatology of monthly zonal mean gravity‐wave forcing from January 2005–December 2010 is presented, along with a discussion of estimated uncertainties and comparison with previous studies. Mesospheric gravity‐wave forcing is found to be underestimated, consistent with the known seasonal evolution of extratropical mesospheric temperature biases within the Met Office assimilated dataset. The sensitivity of gravity‐wave forcing to various parameters within the USSP scheme is investigated. Subsequent experiments diagnose the temperature response in a free‐running version of the Unified Model when mesospheric gravity‐wave forcing is increased through perturbing the energy scalefactor parameter within the USSP scheme and imposing momentum‐flux conservation at the model lid. For physically justifiable perturbations to the USSP scheme, significant temperature responses of ∼10–25 K are seen for mesospheric polar regions under solstice conditions, highlighting the positive impact such changes could possibly have on known temperature biases within the Met Office assimilated dataset.