Impact ofGMS-5andGOES-9Satellite-Derived Winds on the Prediction of a NORPEX Extratropical Cyclone

Abstract

The impact of satellite-derived wind observations on the prediction of a mid-Pacific Ocean cyclone during the North Pacific Experiment (NORPEX, 14 Jan-27 Feb 1998) is assessed using a four-dimensional variational (4DVAR) approach in which a nonhydrostatic version of the Pennsylvania State University-National Center for Atmospheric Research fifth-generation Mesoscale Model (MM5) serves as a strong constraint. The satellitederived wind observations are retrieved through an automated tracking algorithm using water vapor visible, and infrared imagery from the operational Geostationary Meteorological Satellite-5 (GMS-5) and Geostationary Operational Environmental Satellite-9 (GOES-9) over the North Pacific basin. For the case studied, it is found that the amount of satellite wind data is much greater in the upper troposphere than in the lower troposphere.The 4DVAR assimilation of the satellite wind observations is carried out on a single domain with 90-km horizontal resolution. Incorporation of satellite wind observations was found to increase the cyclonic zonal wind shear and the cross-front temperature gradient associated with the simulated cyclone. However, the improvement in the intensity of the simulated cyclone measured by the central sea level pressure is marginal using the same assimilation model. Increasing the forecast model resolution by nesting a 30-km resolution domain yields a more significant impact of the satellite-derived wind data on the cyclone intensity prediction. The GMS-5 satellite winds (upstream data) are found to have more influence on the quality of the cyclone development than the GOES-9 satellite winds (downstream data). An adjoint sensitivity study confirms that the most sensitive region is located upstream of the cyclone, and that the cyclone is more sensitive to the lower rather than the upper atmosphere. Therefore, it is anticipated that larger impacts on cyclone prediction in the mid-Pacific Ocean will occur when a greater or equal amount of satellite wind observations are made available for the lower troposphere as are available for the upper levels.

Recent Innovations in Deriving Tropospheric Winds from Meteorological Satellites

“…While AMVs are prone to greater uncertainty than balloon wind measurements, they have recently been shown to improve numerical analyses and forecasts over ocean areas Langland et al 1999;Soden et al 2001;Xiao et al 2002;Kelly 2004). These data impact studies show the utility of AMVs in helping to resolve meteorological events on scales ranging from large to subsynoptic.…”

Comparisons of Satellite-Derived Atmospheric Motion Vectors, Rawinsondes, and NOAA Wind Profiler Observations

“…With advances in computing power and satellite instrumentation technology, the spatial coverage, accuracy, and detail of the flows depicted from satellites have improved dramatically from the 1960s (Fujita et al 1969) to the present (Velden et al 2005). Objectively determined atmospheric motion vectors (AMVs) have been previously described within a wide variety of meteorological applications, such as NWP model data assimilation (Goerss et al 1998;LeMarshall et al 1996;Leslie et al 1998;Xiao et al 2002;Kelly et al 2004), convective weather forecasting (Negri and Vonder Haar 1980;Rabin et al 2004;Mecikalski and Bedka 2006), and tropical cyclone forecasting (Rodgers and Gentry 1983;Velden et al 1992;Dunion and Velden 2002).…”

Tropical cyclone track forecasting techniques ― A review

“…For example, cloud and water vapor data recorded by satellites have been used to improve the accuracy of numerical forecasts in the Australian region since the early 1980s (Le et al, 1985); satellite-derived wind information has been used to improve the forecast accuracy both for tropical cyclones (Goerss et al, 1998;Isaksen and Stoffelen, 2000;Langland et al, 2009;Leslie et al, 1998;Ma and Tan, 2009;Tomassini et al, 1998;Velden et al, 1992;Wang et al, 2006) and extratropical cyclones (Xiao et al, 2002). Moreover, the internal structure of a cyclone and the amount of water stored in it can be extracted through analyzing satellite images (Kokhanovsky and Hoyningen-Huene, 2004).…”