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To improve our understanding of the similarities and\ndifferences of calculated AMVs, several institutes from around the world\nparticipated in an atmospheric motion vector intercomparison study to test\ntheir methods and strategies in a series of standardized experiments.\nScientists at the University of Wisconsin\u2013Madison Space Science and Engineering\nCenter, in partnership with other American, European, Korean, Japanese and\nBrazilian collaborators, conducted the fourth intercomparison study since 2008.\nThe results of the\nstudy<\/a> appear in the November 2019 Satellite-Derived Wind Observations<\/em>\nspecial issue of Remote\nSensing<\/em><\/a>.<\/em><\/p>\n\n\n\n \u201cThese tests help AMV producers in terms of identifying errors in their algorithms so they can make improvements,\u201d says David Santek, SSEC scientist and co-author. \u201cIn addition, the numerical weather prediction centers, which are the primary users of the data, can see how well the different centers derive their AMVs and give them an idea how they can quality control them with consistent results.\u201d<\/p>\n\n\n\n All of the groups showed improvements since the last study\nwas conducted in 2014. The current study aimed to understand how the next\ngeneration of geostationary satellites \u2013 like Japan\u2019s Himawari-8 and the US\nGOES-16 \u2013 can improve AMV calculations because imagery from the two satellites\nhave greater spatial and temporal resolutions. <\/p>\n\n\n\n AMVs are calculated by analyzing a series of consecutive satellite\nimages. The process involves selecting a \u201ctracer,\u201d a recognizable feature like\na cloud and tracking it over time. A key\nresult from the study showed that accurate cloud-top estimations were an\nimportant indicator for AMV calculations. Wind speed and direction can change\ndrastically depending on the conditions that day and height, making the process\nof determining a cloud\u2019s top less than straightforward.<\/p>\n\n\n\n The study ran a series of three experiments with each of the\nparticipating agencies using satellite imagery from the geostationary satellite\nHimawari-8 and various channels from its Advanced Himawari Imager. In the first\ntwo, specific parameters were put in place to determine how well each of the algorithms\nperformed a specific task. The third experiment was less controlled, allowing\nfor the use of best options to assess AMVs.<\/p>\n\n\n\n Since the 1970s, satellite data have been used to improve\nweather forecasts, at first by hand, and later automated in the 1990s. Santek\nsays these calculations are especially useful for remote areas around the\nworld, where ground-based and radiosonde data are sparse.<\/p>\n\n\n\n![\"\"](\"https:\/\/www.ssec.wisc.edu\/news\/wp-content\/uploads\/sites\/19\/2019\/12\/AMV_Web_Banner-1-1026x390.jpg\")