satellite wind speed data

The RSS data are used to create merged wind products by other researchers.  These are a few examples: The original  V1.1 Cross-Calibrated Multi-Platform Ocean Winds (CCMP) data set is produced by Atlas et al. QuikSCAT data provide high spatial and temporal resolution, near global coverage and extensive validation. Here we describe in detail the QuikSCAT wind vector data produced and distributed by Remote Sensing Systems. Dr. Lucrezia Ricciardulli, Scientist at Remote Sensing Systems, CCMP: Cross-Calibrated Multi-Platform wind vector analysis, SST (AMSR-E): Sea Surface Temperature from Remote Sensing Systems, AVISO: Satellite derived Sea Surface Height above Geoid, Remote Sensing Systems Description of Scatterometer Data Products, JPL PODAAC QuikSCAT Level 3 zonal wind vectors, JPL PODAAC QuikSCAT Level 3 meridional wind vectors, NCAR | National Center for Atmospheric Research, Sample RSS QuikSCAT global daily gridded map (top), for ascending passes only. These effects can cause either positive and negative biases relative to true “wind” signal, they are difficult to model and cannot be easily removed. QuikSCAT, launched in June 1999, remained fully operational until November 2009 when the primary instrument (SeaWinds) antenna stopped rotating due to a mechanical failure of the antenna spin mechanism. Wind speed and direction (polarimetric radiometer and scatterometers): Wind is the movement of air and is caused by the difference in atmospheric pressure between high and low pressure systems.  Over land, we use instruments called anemometers to measure the surface wind speed and wind direction.  These anemometers exist in high-density for many areas and lower-density in less populated regions.  But over the oceans, measurement of surface wind characteristics is far more limited, and is primarily obtained from anemometers located at small island weather stations, on ships, and on buoys floating in the ocean.  Since the ocean regions are so large, especially the Pacific Ocean, knowledge of the wind characteristics over this vast space is important to weather forecasting, ocean navigation, and climate study.  Here is where satellite measurements bring the most critical benefit.  One of the first approaches was to use visible images to study cloud motion and indirectly determine wind speed and direction.  This method is still in use today. Radiometers and scatterometer measurements are instead based on microwave (MW) radiation signals from the ocean surface, as described below. a Near-Real-Time operational product for weather forecasts or data assimilation, or a delayed but more quality-controlled product for climate research). However, radiometers measure only the wind speed at the ocean surface, not the direction. Data can be browsed and downloaded at, where a detailed description of the QuikSCAT dataset is also provided. Product shows the wind vector, consisting of speed and direction, at an assigned height (100-400 mb, 400-700 mb, and below 700 mb) above the Earth's surface based on the infrared energy signatures and guidance from corresponding numerical weather forecast parameters. The process is run on a per image basis as the imagery becomes available. The wind vector retrievals are produced by inverting a semi-empirical Geophysical Model Function (GMF) which relates the backscatter signal to 10m wind speed, wind direction relative to the scatterometer azimuth angle, scatterometer Earth incidence angle, MW signal polarization, and frequency. The quantity provided is a normalized rms after-the-fit residual of the observation minus model backscatter. The Advanced Scatterometer (ASCAT) ocean surface winds are a 10 meter neutral stability wind. The wind speed uncertainty decreases to less than 0.1 m/s when data are averaged globally and at … The wind direction RMS for moderate to high winds (above 6 m/s) is about 10 degrees. They are produced by different institutions for different purposes, often using different GMFs, ambiguity removal methods, and quality control (i.e. Product shows the wind vector, consisting of speed and direction, at an assigned height (600-800 mb and 801-950 mb) above the Earth's surface based on energy signatures and guidance from corresponding numerical weather forecast parameters. Additionally, small data gaps might be present at times due to bad quality or missing data due to the sensor being temporarily turned off. Ricciardulli, L. and F.J. Wentz, 2011b, The New Geophysical Model Function for QuikSCAT: Implementation and Validation, presented at International Ocean Vector Winds Science Team Meeting, Annapolis, MD, May 2011.

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