Operational convective-scale data assimilation over Iran: A comparison between WRF and HARMONIE-AROME |
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| Institution: | 1. Razi University, Kermanshah, Iran;2. Swedish Meteorological and Hydrological Institute, Norrköping, Sweden;3. Institute of Geophysics, University of Tehran, Iran;1. St. Petersburg State University, 7–9, Universitetskaya nab., St. Petersburg 199034, Russia;2. NIERSC, Nansen International Environmental and Remote Sensing Centre, 14th line, 7, St. Petersburg 199034, Russia;3. Arctic and Antarctic Research Institute, Bering str., 38, St. Petersburg 199397, Russia;4. Pacific Oceanological Institute of the Russian Academy of Sciences, 43 Baltiiskaya St., 690041 Vladivostok, Russia;1. St. Petersburg State University, 7/9 Universitetskaya nab, St. Petersburg 199034, Russia;2. Nansen International Environmental and Remote Sensing Centre, 7, 14-th Line V. O., St. Petersburg 199034, Russia;1. Ocean Analysis and Modelling Laboratory, School of Earth, Ocean and Climate Sciences, Indian Institute of Technology Bhubaneswar, Odisha, India;2. Ocean Observation Systems, National Institute of Ocean Technology, Chennai, India |
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| Abstract: | The impact of applying three-dimensional variational data assimilation (3D-Var DA) on convective-scale forecasts is investigated by using two mesoscale models, the Weather Research and Forecasting model (WRF-ARW) and the Hirlam and Aladin Research Model On Non-hydrostatic-forecast Inside Europe (HARMONIE-AROME). One month (1 to 30 December 2013) of numerical experiments were conducted with these two models at 2.5 km horizontal resolution, in order to partly resolve convective phenomena, on the same domain over a mountainous area in Iran and neighboring areas. Furthermore, in order to estimate the domain specific background error statistics (BES) in convective scales, two months (1 November to 30 December 2017) of numerical experiments were carried out with both models by downscaling operational ECMWF forecasts. For setting the numerical experiments in an operational scenario, ECMWF operational forecast data were used as initial and lateral boundary conditions (ICs/LBCs). In order to examine the impact of data assimilation, the 3D-Var method in cycling mode was adopted and the forecasts were verified every 6 hours up to 36 hours for selected meteorological variables. In addition, 24 h accumulated precipitation forecasts were verified separately. Generally, the WRF and HARMONIE-AROME exhibit similar verification statistics for the selected forecast variables. The impact of DA on the numerical forecast shows some evidence of improvement in both models, and this effect decreases severely at longer lead times. Results from verifying the 24 h convective-scale precipitation forecasts from both models with and without DA suggest the superiority of the WRF model in forecasting more accurately the occurred precipitation over the simulation domain, even for the downscaling run. |
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| Keywords: | Convective-scale 3D-Var HARMONIE-AROME WRF Iran |
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