How to get Numerical Weather Prediction Model Initial Conditions From Satellite Ozone Data in Three Easy Steps
Abstract
Satellites provide uniform data coverage globally. Thus, their data have the potential to reduce analysis errors in data sparse areas significantly, thereby improving numerical weather prediction (NWP) forecasts. We describe a methodology to generate NWP model initial conditions (ICs) from satellite total column ozone data based on Davis et al. (1999). This methodology involves the following steps: 1) derive a mean potential vorticity (MPV) field from total column ozone data using correlation coefficients and linear regression least squares best fit line parameters, 2) convert the 2-D MPV field to a 3-D potential vorticity (PV) field using the average PV profile appropriate for each grid point's location and MPV value, 3) invert the 3-D PV field to obtain model ICs (see Davis and Emanuel, 1991). We find that the correlation coefficients vary distinctly with year, latitude and longitude as well as with the analysis and the length of the statistics-generating period used, but that strong correlation coefficients can be obtained despite ozone/MPV time differences as great as seven hours. We also find that ozone-derived vertical PV profiles show good agreement with analysis profiles in cases of comparable MPV values. Davis, C. A., and K. A. Emanuel, 1991: Potential vorticity diagnostics of cyclogenesis. Mon. Wea. Rev., 119, 1929-1953. ________, S. Low-Nam, M. A. Shapiro, X. Zou, and A. J. Krueger, 1999: Direct retrieval of wind from Total Ozone Mapping Spectrometer (TOMS) data: examples from FASTEX. Quart. J. Roy. Meteor. Soc., 125, 3375-3391.
- Publication:
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AGU Spring Meeting Abstracts
- Pub Date:
- May 2006
- Bibcode:
- 2006AGUSM.A53C..01D
- Keywords:
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- 3362 Stratosphere/troposphere interactions;
- 3364 Synoptic-scale meteorology;
- 3315 Data assimilation;
- 3360 Remote sensing