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Linking rapid forecast error growth to diabatic processes

Sánchez, C. ORCID: https://orcid.org/0000-0002-5069-6849, Methven, J. ORCID: https://orcid.org/0000-0002-7636-6872, Gray, S. ORCID: https://orcid.org/0000-0001-8658-362X and Cullen, M. (2020) Linking rapid forecast error growth to diabatic processes. Quarterly Journal of the Royal Meteorological Society, 146 (732). pp. 3548-3569. ISSN 0035-9009

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To link to this item DOI: 10.1002/qj.3861

Abstract/Summary

The predictability of high impact weather events over the North Atlantic is controlled by synoptic‐scale systems and the mesoscale structures embedded within them. Despite forecast uncertainty being greatest at small scales at the initial time, forecast error projects strongly onto synoptic and larger scales within days. Different stages of error growth have previously been identified including: convective instability, baroclinic instability and the influence of divergent outflow on the tropopause position, and interactions between disturbances at tropopause level. Evidence is presented for “predictability barriers” (PBs) identified with events on certain validation dates during the North Atlantic Waveguide and Downstream impact Experiment (NAWDEX) where ensemble spread grows more quickly than usual, but ensemble mean forecast error grows even faster. An advective mechanism for diabatic influence on the development of tropopause ridges is hypothesised to be linked to the PB events. A semi‐geostrophic balance tool is used to attribute the response of the 3‐D ageostrophic flow to geostrophic and diabatic forcing, enabling a novel diagnostic for Diabatically‐Induced Ageostrophic Advection of potential vorticity (DIAA). It is shown that predictability barriers are linked to events with strong diabatic influence on tropopause advection during the NAWDEX period. Error growth exceeds ensemble spread rate by approximately 4/3 during strong DIAA events, showing that predictive skill is considerably lower in these situations.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:91525
Publisher:Wiley

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