An atmospheric dynamics perspective on the amplification and propagation of forecast error in numerical weather prediction models: A case study

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Understanding the root causes of forecast errors and occasional very poor forecasts is essential but difficult. In this paper we investigate the relative importance of initial conditions and model formulation for medium‐range errors in 500 hPa geopotential height. The question is addressed by comparing forecasts produced with ECMWF‐IFS and NCEP‐GFS forecasting systems, and with the GFDL‐fvGFS model initialized with the ECMWF and NCEP initial conditions. This gives two pairs of configurations that use the same initial conditions but different models, and one pair with the same model but different initial conditions. The first conclusion is that the initial conditions play the major role in differences between the configurations in terms of the average root‐mean‐square error for both Northern and Southern Hemispheres as well as Europe and the contiguous US (CONUS), while the model dominates the systematic errors. A similar conclusion is also found by verifying precipitation over low latitudes and the CONUS. The day‐to‐day variations of 500 hPa geopotential height scores are exemplified by one case of a forecast bust over Europe, where the error is found to be dominated by initial errors. The results are generalized by calculating correlations between errors integrated over Europe, CONUS and a region in the southeastern Pacific from the different configurations. For Europe and southeast Pacific, the correlations in the medium range are highest between the pairs that use the same initial conditions, while over CONUS they are highest for the pair with the same model. This suggests different mechanisms behind the day‐to‐day variability of the score for these regions. Over CONUS the link is made to the propagation of troughs over the Rockies, and the result suggests that the large differences in parametrizations of orographic drag between the models play a role.

“…The experimentation here also confirmed that errors in the initial conditions played the major role for the March 2016 ECMWF forecast bust discussed in Magnusson () and Grams et al . ().…”

Section: Discussionmentioning

confidence: 97%

“…We are focusing here on z500 to understand the impact on the synoptic predictability. Medium-range forecast errors in the surface parameters such as 2 m temperature are often dependent on the ability to predict the large-scale flow, such as in the case of the European forecast bust presented in Grams et al (2018).…”

mentioning

confidence: 99%

Dependence on initial conditions versus model formulations for medium‐range forecast error variations

Magnusson

Chen

Lin

et al. 2019

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“…(), who found that this Scandinavian Blocking pattern, which is associated with anomalous warmth in the Eurasian‐Arctic was in part triggered by diabatic heating anomalies in the Gulf Stream region of the North Atlantic, which is consistent with the findings of Grams et al . ().…”

Section: Climatological Forecast Error Growth During Scandinavian Blomentioning

confidence: 99%

Increased Arctic influence on the midlatitude flow during Scandinavian Blocking episodes

Day

Sandu

Magnusson

et al. 2019

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Recent studies have suggested that Arctic teleconnections affect the weather of the midlatitudes on time‐scales relevant for medium‐range weather forecasting. In this study, we use several numerical experimentation approaches with a state‐of‐the‐art global operational numerical weather prediction system to investigate this idea further. Focusing on boreal winter, we investigate whether the influence of the Arctic on midlatitude weather, and the impact of the current Arctic observing system on the skill of medium‐range weather forecasts in the midlatitudes is more pronounced in certain flow regimes. Using so‐called Observing System Experiments, we demonstrate that removing in situ or satellite observations from the data assimilation system, used to create the initial conditions for the forecasts, deteriorates midlatitude synoptic forecast skill in the medium‐range, particularly over northern Asia. This deterioration is largest during Scandinavian Blocking episodes, during which: (a) error growth is enhanced in the European‐Arctic, as a result of increased baroclinicity in the region, and (b) high‐amplitude planetary waves allow errors to propagate from the Arctic into midlatitudes. The important role played by Scandinavian Blocking, in modulating the influence of the Arctic on midlatitudes, is also corroborated in relaxation experiments, and through a diagnostic analysis of the ERA5 reanalysis and reforecasts.

“…The important role of a misrepresented cut‐off evolution leading to large error growth in the further evolution was also discussed by Grams et al . () for a forecast‐bust event in March 2016.…”

Section: Comparison Between Error Growth In the Best And Worst Membersmentioning

confidence: 99%

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

Baumgart

Riemer

2019

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.