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. Five days (30 November - 4 December) of full resolution even satellite (GOES West, METEOSAT-7, and eastern coverage METEOSAT-5) and odd satellite (GMS-5, GOES East, and western coverage METEOSAT-5) IR imagery has been archived. The even and odd satellite configuration preserves the full coverage (140 degrees longitude) of each satellite allowing simultaneous overlap coverage between neighboring satellites. The purpose of this archival is to determine the relationship between two different satellites' advection vectors derived from spatially and temporally collocated imagery, as an alternative to simply performing a time interpolation of a single satellite's advection vectors to compensate for potential dropout periods such as equinox gaps.

B. Existing software which previously derived advection vectors from "best satellite chosen" merged full resolution IR imagery has been modified to produce advection vectors for both even and odd satellite domains. Besides having the ability to create simultaneous vectors from two different satellites, this software is different than the "operational" software used to create the advection vectors for microwave derived precipitation propagation in the following ways:

1. Termination of carryover of advection vectors from one half-hourly time frame into the next half hour for cases when IR imagery was missing or at least one microwave derived precipitation pixel of > 1mm/hr was non existent in the 5x5 degree region.

Previously, carryover was done in order to get the best advection vector for "operational" purposes as opposed to a scientific study of temporal and spatial vector interpolation. Carryover also should have inflated correlations in the previous temporal vector interpolation study. The new modification to determine a vector by half-hourly spatial lag correlation is - at least one IR pixel within the 5x5 degree region must be < 260K, if not, then set the vector value to missing.

2. Maximizing the positive zonal (west-to-east) advection rate from 6 to 12 pixels (8km at equator). This is necessary in both north and south mid-latitudes where both the jet steam advects cloud systems quickly and longitudinal earth distance in an advection pixel decreases substantially poleward of 30 degrees N+S latitude.

3. Software cleanup of exceeding array index maximum problem occurring during spatial lag determination.

C. Produced IR derived half-hourly advection vectors for both even and odd satellite configuration IR imagery for 00:00 GMT 30 November through 00:00 GMT 2 December.

In accordance with section 3 of 26-30 November Work Planned for Next Week,

developed software to statistically compare advection vectors derived from two different satellites. In the data/rjoyce/advect-vectors_2-diff-sats directory on the ftp.ncep.noaa.gov server there are three GrADS plots analyzing vectors for 00:00-23:30 November. One plot each for the zonal and meridional advection comparison, and one for the zonal vectors normalized to 8 km increments (at the equator). In general correlation of both meridional and zonal vectors for all five overlap regions is good, 0.85-0.95 for zonal, 0.80-0.93 for meridional, with the METEOSAT-5 and METEOSAT-7 region the best. Correlation is more variable in the three zones 60N-20N, 20N-20S, and 20S-60S, but still consistent. All satellite pairs track very closely in both absolute vector amplitude and mean vector value for the whole domain and in each zone. RMS between even and odd satellite derived vectors is about 50% of the absolute zonal vector amplitude and between 50% and 100% of the absolute meridional vector amplitude depending on satellite pair. Since the average zonal vector amplitude is 6 pixels for several satellites the north and south zones it is obvious that the zonal advection maximum rate needed to be increased to 12 pixels.

2. WORK PLANNED FOR NEXT WEEK

However interesting these results are, we cannot yet compare statistics of multi-
satellite derived vector comparisons to temporal interpolation of a single satellite's vectors until we perform single satellite temporal interpolation of the new advection vectors created in the even and odd satellite configuration comparison study. Again this is because there is no carryover of advection vectors and an increased zonal maximum advection rate. Not only will correlation be generated, but also normalized bias and normalized RMS so that a direct comparison at each temporal interpolation interval can be made to the relationships already determined between simultaneous vectors derived from two different satellites.

At present one more day of even-odd satellite configuration advection

vectors is needed (3 day minimum) to generate new single satellite temporal vector interpolation statistics.

Also if needed the multi-satellite vector statistical package can temporally

interpolate one satellite's derived vectors and statistically compare against another collocated satellite's vectors.

My personal feeling is the multi-satellite advection vectors will only be

useful over the single satellite temporal interpolation method for gaps larger than equinox periods (~3 hours), we'll know this week. This work will complete the 2nd and 3rd 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.