In this study, it is demonstrated how temperature, humidity, and wind profile data from the lower troposphere obtained with a lightweight unmanned aerial system (UAS) can be used to improve high-resolution numerical weather simulations by four-dimensional data assimilation (FDDA). The combined UAS and FDDA system is applied to two case studies of northeasterly flow situations in southwest Iceland from the international Moso field campaign on 19 and 20 July 2009. Both situations were characterized by high diurnal boundary layer temperature variation leading to thermally driven flow, predominantly in the form of sea-breeze circulation along the coast. The data assimilation leads to an improvement in the simulation of the horizontal and vertical extension of the sea breeze as well as of the local background flow. Erroneously simulated fog over the Reykjanes peninsula on 19 July, which leads to a local temperature underestimation of 8 K, is also corrected by the data assimilation. Sensitivity experiments show that both the assimilation of wind data and temperature and humidity data are important for the assimilation results. UAS represents a novel instrument platform with a large potential within the atmospheric sciences. The presented method of using UAS data for assimilation into high-resolution numerical weather simulations is likely to have a wide range of future applications such as wind energy and improvements of targeted weather forecasts for search and rescue missions.
Abstract.A severe windstorm downstream of Mt. Öraefa-jökull in Southeast Iceland is simulated on a grid of 1 km horizontal resolution by using the PSU/NCAR MM5 model and the Advanced Research WRF model. Both models are run with a new, two equation planetary boundary layer (PBL) scheme as well as the ETA/MYJ PBL schemes. The storm is also simulated using six different micro-physics schemes in combination with the MYJ PBL scheme in WRF, as well as one "dry" run. Output from a 3 km MM5 domain simulation is used to initialise and drive both the 1 km MM5 and WRF simulations. Both models capture gravity-wave breaking over Mt. Öraefajökull, while the vertical structure of the lee wave differs between the two models and the PBL schemes. The WRF simulated downslope winds, using both the MYJ and 2EQ PBL schemes, are in good agreement with the strength of the observed downslope windstorm. The MM5 simulated surface winds, with the new two equation model, are in better agreement to observations than when using the ETA scheme. Micro-physics processes are shown to play an important role in the formation of downslope windstorms and a correctly simulated moisture distribution is decisive for a successful windstorm prediction. Of the microphysics schemes tested, only the Thompson scheme captures the downslope windstorm.
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