GOES-R AWG Land Team: ABI NDVI Algorithm June 15, 2011

1. GOES-R AWG Land Team: ABI NDVI AlgorithmJune 15, 2011 Presented By: Peter Romanov NOAA-CREST City College of New York In collaboration with Dr. Hui Xu, IMSG

2. Outline • Executive Summary • Algorithm Description • ADEB and IV&V Response Summary • Requirements Specification Evolution • Validation Strategy • Validation Results • Summary

3. Executive Summary This NDVI Algorithm generates Normalized Difference Vegetation Index. The NDVI product has been moved from Option 1 to Option 2 list. Algorithm development and validation is performed with MSG SEVIRI data. Versions 4 and 5 of the algorithm have been delivered. CUTR has been conducted. Product has been validated on common dataset. The product accuracy meets the requirements First version of the routine validation tool has been developed and delivered to AIT Full NDVI Algorithm Package (AP) and ATBD at 100% maturity have been delivered last year (09/2010) 3

4. Algorithm Description

5. Algorithm Summary This ABI NDVI Algorithm generates the Option 2 product of Normalized Difference vegetation Index. NDVI is derived at Top of the Atmosphere (TOA) Standard two-channel algorithm, uses ABI bands 2 (0.64µm) and 3 (0.86µm) NDVI is generated hourly NDVI requires daylight and clear sky conditions 5

6. NDVI: Physical Basis • Chlorophyll absorbs solar radiation in the red region of the spectrum • Mesophyll structure of green leaves increases reflectance in the near infrared • Ratio or normalized ratio of RED and NIR reflectance is indicative of the vegetation condition • Larger NDVI means “greener” vegetation • Clouds and snow exhibit low positive or low negative NDVI.

7. NDVI Algorithm Top of the atmosphere NDVI is defined as NDVI=(RNIR-RRED)/(RNIR+RRED) ABI ch.2 and 3 data will be used Retrievals are performed over land surface Retrievals require Clear-sky conditions Daylight No snow cover

8. NDVI Algorithm Output False color composite and the derived NDVI map ofSEVIRI full disk image for April 12, 2007, 12:15 UTC

9. Algorithm Changes from 80% to 100% Metadata output added Quality flags added Delivered in September 2010 9

10. ADEB and IV&V Response Summary General Comment 1: Insufficient validation Response: No real validation of the product is possible since NDVI is not observed in situ. We will continue evaluating temporal consistency of NDVI estimates with ABI proxy datasets to indirectly assess the product validity. General Comment 2: Continue improvement of algorithms Response: The further improvement of the algorithm to derive instantaneous NDVI is not possible. Improvements may concern the development of daily or weekly composited NDVI products, however they are missing in the requirements.

11. ADEB and IV&V Response Summary, Cont’d General Comment 3: Make better use of the GOES advantages: high temporal response, varying solar angle, time continuity, fixed FOV, etc. Response: Current requirements are to derive hourly products. Development of daily or weekly composited products has not been requested. Compositing 15-min imagery to derive hourly product does not make mush sense. General Comment 4: Graceful degradation is not addressed Response: Accepted. However the term should be more clearly defined and possible scenarios of graceful degradation should be agreed upon. 11

12. ADEB and IV&V Response Summary, Cont’d Specific Comment 1: Examine systematic errors by comparing geo NDVI with polar NDVI. Response: This will not reveal systematic errors in geo NDVI since NDVI is a radiance-based parameter. Comparison of geo and polar NDVI may show inconsistencies between two products due to different viewing geometry. This issue has been addressed in our recent work. 12

13. Requirements Requirements Evolution: All requirements are original

14. Validation Strategy

15. NDVI Validation: Accuracy NDVI is a radiance-based parameter NDVI accuracy is defined by radiance measurement accuracy For instrument noise in ch.2 and 3 equivalent to 0.3% NDVI error is below 0.01

16. NDVI Validation: Precision Spatial and temporal change in NDVI should be consistent with variation of the state of the vegetation cover Precision criterion: Low (lack of) high-frequency (day-to-day) changes in NDVI

17. NDVI Validation: Details (1) Method: Evaluate daily change of NDVI NDVI precision specification: 0.04 Approach: Compare NDVI estimates made in cloud-clear conditions at the same time of the day (same geometry) on two consecutive days

18. NDVI Validation: Details (2) Quantitative measures - Daily RMS change of NDVI Validity criteria: - Daily RMS change of NDVI below 0.04

19. NDVI Routine Validation System

20. Validation Results

21. 2006218 2006213 2006223 2006218 2006233 2006238 2006243 NDVI Maps from Common Dataset MSG SEVIRI 11.45 UTC August 2006 21

22. NDVI Time Series from Common Dataset MSG SEVIRI 11.45 UTC August 2006 Large day-to-day variation in derived NDVI values may be due to Missed clouds, Cloud shadows, Dust Other factors (navigation, coregistration, etc.) 22

23. Required precision Required precision Summer 2006 Winter 2007 NDVI Temporal Consistency Test NDVI day-to-day MSRD for all clear sky pixels in SEVIRI FD AIT Common test data set, MSG SEVIRI, 1145 UTC images 23

24. 0.4 0.0 0.2 0.6 0.8 0.4 0.0 0.2 0.6 0.8 Polar vs Geo NDVI Weekly Max Composite, Dates: 2006218-2006225 MSG SEVIRI 4 km NDVI From AIT 4 months run NOAA AVHRR 4 km NDVI Reprojected to SEVIRI grid 24

25. Polar vs Geo NDVI, Cont’d Comparison of Weekly Max NDVI Composites Large disagreement over small and moderate NDVI values is due to substantial cloud contamination of the AVHRR 4km weekly GVIx product. 25

26. Validation Results Summary MSG SEVIRI Common Dataset, August 2006 26

27. Summary The ABI NDVI Algorithm has been developed to provide monitoring of vegetation cover properties with GOES-R ABI Version 5 of the algorithm and ATBD at 100% readiness have been delivered on schedule First version of the routine validation tool was delivered to AIT in December 2010. NDVI product meets the precision specification. 27