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Mesoscale FDDA Experiments with ACARS Data
| Content Provider | Semantic Scholar |
|---|---|
| Author | Chang, Chia-Bo |
| Copyright Year | 2007 |
| Abstract | The focus of this paper is on mesoscale four-dimensional data assimilation (FDDA). Because of its small spatial size, mesoscale weather is strongly influenced by fast-changing local conditions such as cloud cover, friction, and surface heating. To incorporate these fast-changing events so as to maximize the model performance, state-of-the-art mesoscale numerical weather prediction (NWP) often makes use of FDDA of high-frequency observations to update the model state during the time integration (Daley 1991). The NOAA ACARS (Aircraft Communications Addressing and Reporting System) observations taken by commercial aircraft at about every ten minutes crisscrossing the nation (Mamrosh 1998) offer valuable data for mesoscale FDDA. Other researchers such as at NCAR’s Research Applications Laboratory (Sheu et al, 2002; Liu et al, 2004) have provided some previous examination of the impact and quality of ACARS in mesoscale FDDA. A better understanding of how to take advantage of these high resolution data sets can significantly advance our expertise in mesoscale NWP. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://ams.confex.com/ams/pdfpapers/126104.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
