Assistant Technical Representative: John E. Janowiak

Contributors: Robert J. Joyce

Period of Performance: November 19 - 23, 2001

1. WORK PERFORMED DURING THE PAST WEEK

A. Developed software enabling the temporal interpolation of half hourly zonal and meridional IR derived advection vectors (sections 2.A and 2.C in the Work Planned section of last week's report). The method computes the temporal interpolation of both zonal and meridional advection vector components for a controlled spatial domain (individual satellites) at hourly interpolation increments (half hourly past increment combined with half hourly future increment) to be correlated with the original advection vectors for each half hourly advection frame. Correlations from successive half hourly advection periods are averaged to smooth values for each hourly interpolation interval.

B. Tested temporal advection software for the 6-8 August 2001 period for the GOES-10, METEOSAT-7, and METEOSAT-5 satellites for hourly temporal interpolation intervals ranging from 1- 48 hours. Since the total data domain period is 72 hours only 48 half hourly vector frames (00:00 GMT - 23:30 GMT 7 August) were interpolated and correlated to the original vectors. Results of correlations are broken down to zonal and meridional components for the following individual satellites:

Zonal Meridional

Time Interval (hours) GOES-10 MET-7 MET-5 GOES-10 MET-7 MET-5 1	.974 .948	.970	.931	.848 .911

2 .968 .927	.966	.940	.801 .898

3	.959 .918	.955	.925 .742 .863

4	.955 .917 .955	.933	.737 .866

5	.952 .909	.947	.920 .690 .842

6	.950 .905 .947	.911	.702 .848

The results indicate high correlations for the temporal interpolation of zonal advection vectors for the six hourly intervals shown. Values for the GOES-10 domain are possibly higher because of a smaller spatial domain used, thus fewer 5x5 degree latitude regional vector pairs used in the correlations. Correlations for meridional vectors are somewhat smaller but not substantially. Generally meridional vector amplitudes are considerably smaller than zonal and spatial patterns less distinct, so the fact that the temporal correlations are smaller is not surprising. What is strange and a bit of concern is the values for the 4 hour interval compared to 3 hours and 6 hour interval compared to the 5 hour interval is nearly the same (or in some cases higher) for all satellites, this needs a little investigating, after which, GrADS plots need to be created. This study also needs repeating for a different time period, possibly when we get both the even and odd satellite high resolution IR imagery needed in order to compare collocated vector fields derived from separate satellites.

2. WORK PLANNED FOR NEXT WEEK

For the next week, software will be created to analyze the properties of spatial interpolation of the zonal and meridional advection vector fields as a modification of the temporal interpolation software version. Using the previous software as a template allows for spatial interpolation studies over the same domains used in the temporal interpolation studies allowing convenient inter-comparisons. This work will fall under the 2.B and 2.D sections 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.