[1] The paper presents the results of an experimental study of mean fluid flow and turbulence over bed forms in a unidirectional flow with superimposed surface waves. Experiments were performed with only current and with combined wave-current flows over a series of bed forms under different surface wave frequencies for two different Reynolds numbers. Three-dimensional velocity was measured using a 3-D micro acoustic Doppler velocimeter. The superposition of surface waves with increasing frequency leads to an increase in the apparent bottom roughness due to a vortex in the lee, which causes the resistance to the flow. The effect of surface waves is to increase the flow stability, consequently reducing flow separation and enhanced mixing in the lee side of the bed form. A stronger circulation pattern in the lee side of the bed forms is observed at a higher Reynolds number.Citation: Ojha, S. P., and B. S. Mazumder (2010), Turbulence characteristics of flow over a series of 2-D bed forms in the presence of surface waves,
The present study concentrates on the assimilation of clear‐sky radiances from the recently launched INSAT‐3D satellite. The imager and sounder are two primary meteorological instruments aboard the INSAT‐3D satellite. Pre‐assimilation monitoring of the radiances has been carried out from April to July 2014. A double‐difference technique using the High Resolution Infrared Sounder (HIRS) on MetOp‐A is employed to remove the effect of deficiencies in the model‐analysed profiles which can contribute to the biases. Observed radiances of both instruments appear to be colder (∼1.5–2 K) with respect to radiative transfer model (RTM) simulated radiances, except water vapour channel radiances, which are warmer (0.5–1 K). The standard deviations of observed minus RTM‐simulated radiances are between 0.5 and 1.5 K. Prior to data assimilation, these biases are corrected using a variational bias correction scheme. The largest impacts on the analyses, when assimilating imager radiances, are found in the mid‐ and upper‐tropospheric moisture, while assimilation of sounder radiances impacted both moisture and temperature throughout the troposphere. The more accurate analyses with the INSAT‐3D radiance assimilation lead to improved moisture, wind, temperature and precipitation forecasts compared to the control case in which only conventional observations were assimilated. The results demonstrate the ability of temperature‐ and water vapour‐sensitive radiances to improve not only the temperature and moisture fields, but also the wind fields, enhancing their importance, particularly over tropical regions where wind observations are more important.
Radio signals transmitted from a satellite constellation and gathered by a ground-based Global Navigation Satellite System (GNSS) receiver allow computation of zenith tropospheric delay (ZTD), which is related to the atmospheric moisture. This study investigates the impact of assimilating ZTD obtained from a ground-based GNSS network on a numerical weather prediction model analyses and subsequent forecasts quality. The numerical data assimilation experiments are performed using three-dimensional variational data assimilation system in the Weather Research and Forecasting model, at 10-km horizontal grid spacing for the entire month of July 2017. A comparison with European Centre for Medium-Range Weather Forecast analyses shows a clear positive impact of ZTD assimilation on the lower to middle tropospheric moisture, upper air temperature, and middle and upper tropospheric wind; errors are reduced by as large as 4%, when compared to the model run without ZTD assimilation. The impact on the analyses and forecast quality of surface meteorological variables is mostly neutral with some indication of positive impact on surface pressure. An improvement in the rainfall forecasts is also noticed when model assimilates ZTD observations. In addition, the impact of the formulation of forward model, which calculates model equivalent of the GNSS ZTD, has been assessed on ZTD assimilation. A revised forward model has been implemented within the Weather Research and Forecasting assimilation system. The revised forward model outperforms the original model for ZTD assimilation. Overall result implies that GNSS ZTD data has a good potential for improving the weather prediction and advocates the strengthening of the ground-based GNSS network over the Indian region, which is currently very sparse.A number of satellites are currently equipped with humidity sensors, including Microwave Humidity Sounder, Special Sensor Microwave Imager Sounder, Advanced Microwave Scanning Radiometer, the Key Points:• A revised forward model has been implemented for the assimilation of zenith tropospheric delay (ZTD) observations into the WRF model • Assimilation of ZTD using the revised forward model shows higher positive impact as compared to the original observation operator • The assimilation of ZTD from ground-based GNSS receivers has a great potential to improve the weather prediction over the Indian regionCorrespondence to:
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