The assimilation of horizontal line‐of‐sight wind information into the ECMWF data assimilation and forecasting system. Part I: The assessment of wind impact

Abstract

In preparation for the Aeolus Doppler Wind Lidar satellite mission, single‐component wind information from conventional observations was assimilated into the ECMWF data assimilation system. Various Observing System Experiments have been designed and performed in order to estimate the impact of such information in numerical weather prediction. The evaluation used various adjoint diagnostic tools and traditional statistical verification methods. The importance of assimilating wind observations as either single component or full vector wind is evaluated. Comparisons between the assimilation of wind and mass observations were also made. Wind observations can lead to significant improvement in the upper troposphere, lower stratosphere and in the Tropics. Mass data are more valuable in the midlatitudes, particularly in the lower part of the atmosphere. The comparison of additional mass and wind observations in the Global Observing System is useful to understand the importance of future wind observations. The investigation also highlighted that the impact of zonal wind observations is larger than the meridional wind (Aeolus will mostly measure wind components near the zonal direction). Root mean‐squared errors of temperature and wind forecasts when the single wind component (zonal) is assimilated show around 35% degradation up to day 2 forecasts and around 20% after day 2 as compared to assimilating full vector wind. Therefore the single (zonal) wind components can provide a large fraction of the vector wind impact particularly for the medium‐range forecast, which is promising for Aeolus.

Impact of local data assimilation on tropical cyclone predictions over the Bay of Bengal using the ARW model

“…The improvements in intensity with radiance data (temperature and moisture) are evident due to improvements in the model thermodynamics. Earlier studies (Kalnay et al, 1985;Cress and Wergen, 2001;Horanyi et al, 2014) have reported the importance of wind observations compared to mass observations in the tropics in assimilation and forecast systems. The present results show higher impacts of motion vectors relative to radiances in TC predictions.…”

Assessment of virtual towers performed with scanning wind lidars and Ka-band radars during the XPIA experiment

“…The increasing need of monitoring the atmospheric boundary layer for a broad range of technological and scientific pursuits -such as for meteorology (Banta et al, 2002;Calhoun et al, 2006;Emeis et al, 2007;Horanyi et al, 2015;Vanderwende et al, 2015;Bonin et al, 2015), renewable energy (Thresher et al, 2008;Jones and Bouamane, 2011;Aitken et al, 2014;Iungo, 2016) and air traffic management (George and Yang, 2012;Smalikho and Banakh, 2015) -has led to a rapid development of remotesensing measurement techniques, such as wind lidars Cariou, 2015;Simley and Pao, 2012;Iungo andPorté-Agel, 2013, 2014) and radars (Farnet and Stevens, 1990;O'Hora and Bech, 2007;Hirth and Schroeder, 2013;Hirth et al, 2015). Compared to classical meteorological towers, remote-sensing instruments allow easier deployment, enhanced capability of varying deployment locations and potentially lower costs.…”

WIVERN: A New Satellite Concept to Provide Global In-Cloud Winds, Precipitation, and Cloud Properties

“…Previous studies suggest that line-of-sight winds have 70% of the value of full vector winds (Horányi et al 2015a) and that "sensitive" areas where observations are needed to improve forecasts are often cloudy (McNally 2002). Preparatory mission studies confirm that any artifacts associated with the polarization diversity technique should be rare and can easily be identified and rejected.…”

“…The winds from WIVERN are only line of sight but Horányi et al (2015a) have demonstrated that, with a state-of-the-art data assimilation system and real observations, HLOS winds such as would be obtained from an aircraft provide about 70% of the impact of a vector wind, and that in the tropics the impacts of wind data are much greater than the mass information. McNally (2002) provides further evidence for the potential impact of in-cloud winds.…”

“…Simulations carried out to predict the potential impact of the winds from the Aeolus satellite by Horányi et al (2015b) have shown that assimilating winds that are biased by 1-2 m s −1 when the random error standard deviation is around 2 m s −1 will actually degrade the forecast unless the bias can be estimated and removed prior to assimilation. Our analysis suggests that winds from WIVERN should only be biased when they are affected by ground clutter and that such regions should be easy to identify.…”