Processes governing the amplification of ensemble spread in a medium‐range forecast with large forecast uncertainty

Abstract

This study provides a process‐based perspective on the amplification of forecast uncertainty and forecast errors in ensemble forecasts. A case from the North Atlantic Waveguide and Downstream Impact Experiment that exhibits large forecast uncertainty is analysed. Two aspects of the ensemble behaviour are considered: (a) the mean divergence of the ensemble members, indicating the general amplification of forecast uncertainty, and (b) the divergence of the best and worst members, indicating extremes in possible error‐growth scenarios. To analyse the amplification of forecast uncertainty, a tendency equation for the ensemble variance of potential vorticity (PV) is derived and partitioned into the contributions from individual processes. The amplification of PV variance is, on average for the midlatitudes of the Northern Hemisphere, dominated by near‐tropopause dynamics. Locally, however, other processes can dominate the variance amplification, for example, in the region where tropical storm Karl interacts with the Rossby‐wave pattern during extratropical transition. In this region, the variance amplification is dominated by upper‐tropospheric divergence and tropospheric–deep interaction and is thereby mostly related to (moist baroclinic) cyclone development. The differences between the error growth in the best and worst ensemble members can, to a large part, be attributed to differences in the representation of cut‐off evolution around 3 days, which subsequently amplifies substantially in the highly nonlinear region of the Rossby‐wave pattern until 5 days. In terms of the processes, the differences in error growth are dominated by differences in the error growth by near‐tropopause dynamics. The approach presented provides flow‐dependent insight into the dynamics of forecast uncertainty and forecast errors and helps to understand better the different contributions of specific weather systems to the medium‐range amplification of ensemble spread.

The three-dimensional life cycles of potential vorticity cutoffs: a global and selected regional climatologies in ERA-Interim (1979–2018)

“…Several approaches exist to identify COLs. Classically, they are identified as closed geopotential height contours in the mid or upper troposphere (e.g., Bell and Bosart, 1989;Nieto et al, 2005;Munoz et al, 2020). COLs are also associated with an anomalously low tropopause, i.e., with stratospheric air in regions that are climatologically tropospheric.…”

“…Due to the large variety of near-tropopause cyclonic vortices on the globe, there is no clear consensus in the scientific literature which vortices are to be considered COLs. While many studies focused on COLs located equatorward of the jet stream, others showed that there exist mid-and upper-level closed cyclones poleward of the jet stream, e.g., over the Hudson Bay, south of Greenland, and the North Pacific (Bell and Bosart, 1989;Parker et al, 1989;Kentarchos and Davies, 1998;Wernli and Sprenger, 2007;Munoz et al, 2020). Munoz et al (2020) provided the first climatology of COLs that covers both hemispheres (albeit restricted to the mid-latitudes) and captured the classical COLs at lower latitudes as well as COLs at higher latitudes by considering two pressure levels (200 and 500 hPa).…”

“…The frequencies, geographical distribution, seasonality, and tracks of the "classical" COLs equatorward of the jet stream are well known in both hemispheres. Hotspots in the Northern Hemisphere are the eastern North Pacific, eastern North Atlantic and the Mediterranean, and northern China-Siberia (Bell and Bosart, 1989;Kentarchos and Davies, 1998;Nieto et al, 2005). In the Southern Hemisphere, they tend to occur around the main land masses, i.e., South America, South Africa, and Australia/New Zealand (Fuenzalida et al, 2005;Reboita et al, 2010;Pinheiro et al, 2017).…”

“…Most COLs have lifetimes of 2-3 d and generally travel eastward. Some studies suggested that they are very mobile and travel hundreds of kilometers (Kentarchos and Davies, 1998;Nieto et al, 2005;Reboita et al, 2010), whereas others point out their quasi-stationarity (Bell and Bosart, 1989;Pinheiro et al, 2017). A few regional studies have also investigated the vertical evolution of COLs and the extension of their circulation to the surface (e.g., Porcu et al, 2007;Pinheiro et al, 2020).…”

Linking rapid forecast error growth to diabatic processes

“…The concept of interaction between Rossby waves at different levels through isentropic advection by the wind attributed to different wave components is central to an explanation of baroclinic instability (Heifetz et al ., 2004). Surprisingly, when the methodology was applied to the operational ECMWF ensemble forecasts by Baumgart and Riemer (2019), they found the baroclinic interaction between low‐level temperature anomalies and tropopause‐level PV anomalies to be a weak contributor to the overall error growth in the ensemble, even though this interaction dominates the growth of the weather systems themselves. However, an important consideration here is that the divergent flow was found from Helmholtz decomposition of the full wind in the model and therefore contains the influence of ageostrophic motion associated with baroclinic wave dynamics, as well as the enhanced divergent outflow attributable to diabatic heating and unbalanced divergent motions (such as gravity waves).…”