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Kosmos
Astronomia Astrofizyka
Inne

Kultura
Sztuka dawna i współczesna, muzea i kolekcje

Metoda
Metodologia nauk, Matematyka, Filozofia, Miary i wagi, Pomiary

Materia
Substancje, reakcje, energia
Fizyka, chemia i inżynieria materiałowa

Człowiek
Antropologia kulturowa Socjologia Psychologia Zdrowie i medycyna

Wizje
Przewidywania Kosmologia Religie Ideologia Polityka

Ziemia
Geologia, geofizyka, geochemia, środowisko przyrodnicze

Życie
Biologia, biologia molekularna i genetyka

Cyberprzestrzeń
Technologia cyberprzestrzeni, cyberkultura, media i komunikacja

Działalność
Wiadomości | Gospodarka, biznes, zarządzanie, ekonomia

Technologie
Budownictwo, energetyka, transport, wytwarzanie, technologie informacyjne

Impact of radar data assimilation for the simulation of a heavy rainfall case in central Italy using WRF–3DVAR

Impact of radar data assimilation for the simulation of a heavy rainfall case in central Italy using WRF–3DVARAtmospheric Measurement Techniques, 7, 2919-2935, 2014Author(s): I. Maiello, R. Ferretti, S. Gentile, M. Montopoli, E. Picciotti, F. S. Marzano, and C. FaccaniThe aim of this study is to investigate the role of the assimilation of
Doppler weather radar (DWR) data in a mesoscale model for the forecast of a
heavy rainfall event that occurred in Italy in the urban area of Rome from
19 to 22 May 2008. For this purpose, radar reflectivity and radial
velocity
acquired from Monte Midia Doppler radar are assimilated into the Weather
Research Forecasting (WRF) model, version 3.4.1. The general goal is to
improve the quantitative precipitation forecasts (QPF): with this aim,
several experiments are performed using the three-dimensional variational
(3DVAR) technique. Moreover, sensitivity tests to outer loops are performed
to include non-linearity in the observation operators.

In order to identify the best initial conditions (ICs), statistical
indicators such as forecast accuracy, frequency bias, false alarm rate and
equitable threat score for the accumulated precipitation are used.

The results show that the assimilation of DWR data has a large impact on both
the position of convective cells and on the rainfall forecast of the analyzed
event. A positive impact is also found if they are ingested together with
conventional observations. Sensitivity to the use of two or three outer loops
is also found if DWR data are assimilated together with conventional data.

Atmospheric Measurement Techniques 2014/09/12 - 22:30 Czytaj