Recalculation of error growth models' parameters for the ECMWF forecast system

Bednář, Hynek; Raidl, Aleš; Mikšovský, Jiří

doi:10.5194/gmd-14-7377-2021

Cited by 2 publications

(2 citation statements)

References 24 publications

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“…(1995), Boer (1994), Dalcher and Kalnay (1987) and more recently by Bednaf et al . (2021). Of special interest in the context of the present study is the decrease of the error growth (see upper panels in Figures 5–8) towards the end of the 10‐day atmospheric forecasts.…”

Section: Discussionmentioning

confidence: 99%

“…This type of model errors evolution with lead time is reminiscent of earlier studies focused on documenting and understanding the error growth in atmospheric medium-range forecasts. This includes studies first by Lorenz (1982), followed by Simmons et al (1995), Boer (1994), Dalcher and Kalnay (1987) and more recently by Bednaf et al (2021). Of special interest in the context of the present study is the decrease of the error growth (see upper panels in Figures 5-8) towards the end of the 10-day atmospheric forecasts.…”

Section: The Role Of Variability: Linking Stde and Temporal Correlationmentioning

confidence: 91%

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Evaluating the impact of land surface on medium‐range weather forecasts using screen‐level analyses

Bélair

Alavi

Carrera

et al. 2023

Quart J Royal Meteoro Soc

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In this study screen‐level analyses of air temperature and humidity are used to objectively evaluate the impact of a new land‐surface package being considered for implementation in Environment and Climate Change Canada (ECCC)'s medium‐range global deterministic numerical weather prediction (NWP) system. Through its control of heat, moisture, and momentum fluxes to the atmosphere, the land surface has a substantial impact on near‐surface meteorology and on the atmospheric boundary layer. The approach examined in this study is based on the comparison between model forecasts and screen‐level analyses. It demonstrates the impact on medium‐range NWP of a new land‐surface package that includes (i) a new set of databases to specify soils and land‐cover characteristics, (ii) improved land‐surface initial conditions obtained by the assimilation of space‐based remote‐sensing observations, and (iii) a more sophisticated scheme for land‐surface modelling. The evaluation method is shown to provide useful information on the impact of the new land‐surface package, including lead‐time‐averaged difference maps as well as plots showing the evolution with lead time of the standard deviation of errors (STDE) and of the temporal correlation between forecasts and analyses. The new land‐surface package has a positive impact on near‐surface forecasts of air temperature and humidity for a summertime period, with smaller STDE and larger temporal correlation for both variables. The improvement is greater for humidity than for air temperature. The maximum impact is found around seven‐day lead time, with substantial gains in absolute and relative values for STDE and temporal correlation. The positive impact is also quantified in terms of prediction hours, with gains of about one day at the medium range. Details of the pros and cons for this objective evaluation approach are discussed.

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Section: Discussionmentioning

confidence: 99%

Section: The Role Of Variability: Linking Stde and Temporal Correlationmentioning

confidence: 91%

Evaluating the impact of land surface on medium‐range weather forecasts using screen‐level analyses

Bélair

Alavi

Carrera

et al. 2023

Quart J Royal Meteoro Soc

View full text Add to dashboard Cite

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Prediction error growth in a more realistic atmospheric toy model with three spatiotemporal scales

Bednář

Kantz²

2022

Geosci. Model Dev.

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Abstract. This article studies the growth of the prediction error over lead time in a schematic model of atmospheric transport. Inspired by the Lorenz (2005) system, we mimic an atmospheric variable in one dimension, which can be decomposed into three spatiotemporal scales. We identify parameter values that provide spatiotemporal scaling and chaotic behavior. Instead of exponential growth of the forecast error over time, we observe a more complex behavior. We test a power law and the quadratic hypothesis for the scale-dependent error growth. The power law is valid for the first days of the growth, and with an included saturation effect, we extend its validity to the entire period of growth. The theory explaining the parameters of the power law is confirmed. Although the quadratic hypothesis cannot be completely rejected and could serve as a first guess, the hypothesis's parameters are not theoretically justifiable in the model. In addition, we study the initial error growth for the ECMWF forecast system (500 hPa geopotential height) over the 1986 to 2011 period. For these data, it is impossible to assess which of the error growth descriptions is more appropriate, but the extended power law, which is theoretically substantiated and valid for the Lorenz system, provides an excellent fit to the average initial error growth of the ECMWF forecast system. Fitting the parameters, we conclude that there is an intrinsic limit of predictability after 22 d.

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Recalculation of error growth models' parameters for the ECMWF forecast system

Cited by 2 publications

References 24 publications

Evaluating the impact of land surface on medium‐range weather forecasts using screen‐level analyses

Evaluating the impact of land surface on medium‐range weather forecasts using screen‐level analyses

Prediction error growth in a more realistic atmospheric toy model with three spatiotemporal scales

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