Accessibility navigation

Representation of western disturbances in CMIP5 models

Hunt, K. M. R. ORCID:, Turner, A. G. ORCID: and Shaffrey, L. C. ORCID: (2019) Representation of western disturbances in CMIP5 models. Journal of Climate, 32. pp. 1997-2011. ISSN 1520-0442

Text - Accepted Version
· Please see our End User Agreement before downloading.


It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1175/JCLI-D-18-0420.1


Western disturbances (WDs) are synoptic extratropical disturbances embedded in the subtropical westerly jet stream. They are an integral part of the South Asian winter climate, both for the agriculture-supporting precipitation they bring to the region and for the associated isolated extreme events that can induce devastating flash flooding. Here, WD behaviour and impacts are characterised in 23 CMIP5 historical simulations and compared with reanalysis and observations. It is found that WD frequency has a strong relationship with model resolution: higher resolution models produce significantly more WDs, and a disproportionately high fraction of extreme events. Exploring metrics of jet strength and shape, we find that the most probable cause of this relationship is that the jet is wider in models with coarser resolution, and therefore the northern edge in which WDs are spun up sits too far north of India. The frequency of WDs in both winter and summer is found to be overestimated by most models, and thus the winter frequency of WDs estimated from the multi-model mean (30 winter−1) is above the reanalysis mean (26 winter−1). In this case, the error cannot be adequately explained by local jet position and strength. Instead, we show that it is linked with a positive bias in upstream mid-tropospheric baroclinicity. Despite a positive winter precipitation bias in CMIP5 models over most of India and Pakistan and a dry bias in the western Himalaya, the fraction of winter precipitation for which WDs are responsible is accurately represented. Using partial correlation, it is shown that the overestimation in WD frequency is the largest contributor to this bias, with a secondary, spatially heterogeneous contribution coming from the overestimation of WD intensity.

Item Type:Article
Divisions:Science > School of Mathematical, Physical and Computational Sciences > NCAS
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:79064
Publisher:American Meteorological Society


Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation