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Impact of land surface stochastic physics in ALADIN‐LAEF (CROSBI ID 269720)

Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija

Wang, Yong ; Belluš, Martin ; Weidle, Florian ; Wittmann, Christoph ; Tang, Jian ; Meier, Florian ; Xia, Fan ; Keresturi, Endi Impact of land surface stochastic physics in ALADIN‐LAEF // Quarterly Journal of the Royal Meteorological Society, 146 (2019), 1-18. doi: 10.1002/qj.3623

Podaci o odgovornosti

Wang, Yong ; Belluš, Martin ; Weidle, Florian ; Wittmann, Christoph ; Tang, Jian ; Meier, Florian ; Xia, Fan ; Keresturi, Endi

engleski

Impact of land surface stochastic physics in ALADIN‐LAEF

To deal with the land surface physics uncertainties, a stochastic scheme basedon stochastic perturbation of physics tendencies is implemented and tested. Theimpact of land surface physics uncertainties and their relative importance to landsurface initial uncertainties are investigated in the regional ensemble forecast-ing system ALADIN-LAEF (Aire Limitée Adaptation Dynamique DéveloppementInterNational – Limited Area Ensemble Forecasting). The land surface initial per-turbation is generated by using an ensemble of land surface data assimilation ; andthe land surface physics uncertainties by applying the idea of stochastically per-turbed parametrization tendencies (SPPT) scheme. Three experiments are conductedand compared with the reference ensemble over a 2-month period. The results showthe introduction of land surface stochastic physics increases the ensemble spread, reduces the ensemble bias, and keeps neutral in deterministic forecast skill of theensemble, its impact strongly depending on the quality of ensemble initial condi-tions. The ensemble land surface data assimilation has stronger positive impact onthe ALADIN-LAEF than the land surface stochastic physics for screen-level tem-perature and humidity. There is not much impact on 10 m wind and precipitation.Best results are obtained when both the ensemble land surface data assimilation andland surface stochastic physics are used simultaneously ; it gives a more reliable andstatistically consistent forecast, which is contributed mainly by ensemble land sur-face data assimilation in the first forecast hours and largely by land surface stochasticphysics in the later forecast hours.

ensemble prediction, land surface physics, numerical weather prediction, probabilistic forecast, stochastic physics, surface perturbation

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Podaci o izdanju

146

2019.

1-18

objavljeno

0035-9009

1477-870X

10.1002/qj.3623

Povezanost rada

Geofizika

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