Assistant Technical Representative: John E. Janowiak

Contributors: Robert J. Joyce

Period of Performance: November 26 - 30, 2001

1. WORK PERFORMED DURING THE PAST WEEK

A. Refined software temporally interpolating half hourly zonal and meridional IR derived advection vectors by adding logic to resolve interpolations ending in .5 increments. Since advection vectors are discrete, either rounding up or down previously biased the interpolated vectors, affecting correlation with original vectors. The biased was eliminated and temporal correlations slightly increased by choosing to round the interpolated vector towards the amplitude of the vector (of the two used in the temporal interpolation) with the higher spatial lag correlation. Since the temporal distance from both the past and future value used in interpolation is the same (currently fixed) it makes sense to use the vector with higher spatial lag correlation to resolve the rounding issue.

B. Tried fervently to determine why correlations of 4 hour temporal interpolations are nearly the same as those of 3 hours, and correlation of 6 hour interpolations as high as those 5 hour interpolations (check last week's report tables). The strange thing is that correlations at the 1 hour interval (both zonal and meridional) are always the highest, followed by the 2 hour interval. A 1 hour interval means that for missing 12:00-12:30 GMT advection vectors, interpolation is performed between the 11:30-12:00 GMT and the 12:30-13:00 advection vectors. Note that the intervals (even hours) with slightly higher than expected correlations are temporally interpolated from vectors derived from IR imagery scanned at the same minutes of the hour as the advection period for which the interpolation is being performed, i.e. correlation of 10:00-10:30 GMT and 14:00-14:30 GMT interpolated vectors with the original 12:00-12:30 GMT vectors is about the same as the relationship of 10:30-11:00 GMT and 13:30-14:00 GMT interpolated vectors with original 12:00-
12:30 GMT vectors, both zonally and meridionally. There is no difference in these relationships if the interpolations are separated for beginning of the hour and end of the hour advection vectors, either in advection vector amplitude, correlation amplitude, or correlation dominance relative to interval.

C. Developed software spatially interpolating zonal and meridional IR derived advection vectors for a specified region within a particular satellite's domain. By using the temporal interpolation software as the beginning template, convenient inter-comparisons of temporal and spatial interpolation can be made over collocated domains. The interpolated values were then categorized by the distance of the nearest value used in the interpolation process by ~550 km intervals, the resolution of vectors at the equator (~5 degrees latitude/ longitude). This work will falls under the 2.B and 2.D sections below. Resulting correlations of spatial interpolation show good correlation (~0.70 - 0.9) in the first few distance intervals for zonal advections vectors for the GOES West, METEOSAT-7, and METEOSAT-5 satellites, but not as high as temporal interpolation correlations for the first few hourly intervals (~0.90-0.98). Spatial interpolation correlation values for meridional advection vectors (~0.4 - 0.7) in the first few distance intervals were considerably smaller than temporal interpolation (0.75-0.93). For both zonal and meridional IR derived advection vectors, correlation drops off much quicker with spatial interpolation relative to temporal interpolation, leaving usefulness of spatial interpolation to cases when a geostationary satellite is inoperative for a substantial period of time.

2. WORK PLANNED FOR NEXT WEEK

For the next week, even and odd satellite configuration, full resolution IR imagery will be archived for determination the relationship of collocated advection vectors produced by different satellites. The even and odd satellite configuration preserves the full coverage of each satellite allowing simultaneous overlap between neighboring satellites. Software will then be modified in order to produce advection vectors from more than one satellite and for comparison. This work will fall under the 3rd section below.

A. The overall goal is to get the best half hourly global advection field, at all locations.

1. The assumption that this must begin with preforming spatial lag correlations at lag of only a half hour between successive images (or hourly only in GMS domain) must be proved. Show the decay in correlation by increasing the temporal lag between successive images. The resulting spatial lag correlation at each location should be averaged for each temporal lag increment. Also, smoothed maps of temporally lagged correlation are produced by averaging several maps of correlation at the same lag for a view of regional dependency.

2. The assumption that advection vector correlation changes quicker spatially than temporally must be proven. This can be shown by:

A. Start with 13 successive half hourly advection vector maps and focus over an

area derived from spatially and temporally complete IR images say over the GOES 8 domain. Take a copy of the 7th vector field and remove a large interior section.

B. Replace the missing field first by performing a bilinear interpolation within the missing array. Then correlate all interpolated values to the original vectors at each interpolation distance interval to gauge the degradation of spatial interpolation with distance.

C. Replace the missing field by a linear temporal interpolation from the 6th and 8th vector fields (one half hour past and future). Repeat the procedure by interpolating from vector fields at increased half hourly increments, (i.e. 5th and 9th, 4th and 10th). Correlate only the replaced portion of the vector field for each temporal interpolation increment with the original vector array to gauge the degradation of correlation with incrementing temporal interpolation distance.

D. Compare the effects of spatially interpolating advection vectors to temporal interpolation at the various intervals shown above (B&C), to be potentially used in tandem varying upon spatial and temporal dependencies.

3. Compare collocated vector fields derived from separate satellites. In order to do this parallax and zenith angle corrected full resolution IR from both the even and odd geostationary satellite configuration must be written to disk. This is necessary in order to perform spatial lag correlation separately for both geostationary satellites in their overlap regions for the same period of time. Comparisons of these vector fields derived from separate satellites will determine if an additional satellite will improve the vector field, in an overlap region, if the dominant satellite displays large temporal gaps in imagery. These results should be compared to spatial and temporal interpolation properties of single satellite derived vector fields (2B&C) to determine usefulness.

4. Repeat procedure tallying all IR images per day at 5.0 degree latitude/longitude region for the dominant satellite (#1 Work Performed Past Week) by including all satellites observing the region.