1. Comparisons of MODIS and GPS Precipitable Water: Outlook for Coastal Assimilation Studies Jennifer Haase, Eric Calais, Debbie Shutts, Andy Snyder Purdue University Department of Earth and Atmospheric Sciences

2. Objectives The long term goal is to test potential forecast improvements by assimilating satellite moisture data such as SSM/I, MODIS and GPS precipitable water for cases such as hurricane Lili (joint work with Shu-Hua Chen, UC Davis) The near term objective is to evaluate the quality of the MODIS precipitable water data, especially for tropical storms

3. Hurricane Lili - Synoptic Overview Lili was a classic Cape Verde storm that attained a maximum intensity of 125 kt (S-S Category 4) over the northern Gulf of Mexico The storm caused considerable flooding in portions of the Caribbean Islands Portions of Jamaica received more than 60 cm of rainfall 13 deaths were attributed to Lili, and the total damage estimate approached $0.9 billion Her landfall on the central Louisiana coast was preceded by Tropical Storm Isidore only one week before - Statistics provided by the NHC Terra’s view of Hurricane Lili on the afternoon of 2 October, 2002 over the central Gulf of Mexico (NASA-GSFC)

4. Synoptic Overview Lili first became a tropical storm over the central Atlantic on 23 September, 2002 The storm intensified slowly in the western Atlantic. As Lili emerged into the Gulf, pressures steadily dropped and it rapidly developed into a Category 4 hurricane just south of Louisiana Figures from the NOAA Hurricane Center (NHC)

5. Hurricane Lili - Synoptic Overview Figures from the NOAA Hurricane Center (NHC) Lili weakened even more rapidly than she strengthened Barely a hurricane when making landfall near Intracoastal City in southern LA on 3 October

6. Forecasting challenges Current forecasting of hurricane tracks is done well Forecasting of hurricane intensity is not done well, especially for storms that intensify rapidly Hurricane Lili is an example of such a case Intensified from Cat. 2 to Cat. 4 in 24 hours, then weakened from Cat. 4 to Cat. 1 in 13 hours Jin and Liou, 2004

7. Forecasting challenges Improved prediction of the storm intensification was achieved in a high resolution run (Jin and Liou, 2004), using a microphysics scheme that includes graupel. Successful simulation of the eyewall reorganization and good prediction of the TRMM precipitation data. Weakening still not well predicted. Tested sensitivity to SST and vertical wind shear but these could only account for about 27% of the weakening. Are other possible factors the moisture field, including the down stream environment or variations stemming from Isadore’s passage?

8. MODIS sensor on Terra / Aqua NASA, Terra & Aqua –launched 1999, 2002 –705 km polar orbits, descending (10:30 a.m.) & ascending (1:30 p.m.) Sensor Characteristics –36 spectral bands ranging from 0.41 to 14.385 µm –cross-track scan mirror with 2330 km swath width –Spatial resolutions:  250 m (bands 1 - 2)  500 m (bands 3 - 7)  1000 m (bands 8 - 36) –2% reflectance calibration accuracy –onboard solar diffuser & solar diffuser stability monitor Images from NASA, King, 2003

9. MODIS moisture data The near-infrared total-column precipitable water is derived from the attenuation of reflected solar light from the surface. The reflected signal is very sensitive to boundary-layer water vapor The product is available only over areas where there is a reflective surface in the near IR. PW in the nIR is retrievable during the day over land where the surface type is known and over sea surfaces that experience sun glint 1-km spatial resolution of the MODIS instrument is available only for the near IR 5×5 1-km pixel resolution is available both day and night using the infra-red algorithm when at least nine FOVs are cloud free. The daily level-2 near-IR PW product (1-km resolution), and the daily, 8- day, and monthly level 3 products (1º resolution, global) are routinely produced and archived at a NASA computing facility

10. MODIS near-IR Retrieval MODIS is the first space instrument to use near-IR bands together with the traditional IR bands to retrieve PW in the atmospheric column Studies so far have shown an accuracy of 5-10% The sources of error include the spectral reflectance of the land/sea surface, sensor radiometric and spectral calibrations, pixel registration between several channels, atmospheric temperature and moisture profiles, and haze Gao and Kaufman (2003) and others have found the largest errors to be from uncertainty in the reflectance of land surfaces and in the amount of haze over darker surfaces From Gao and Kaufman (2003)

11. Previous Comparisons Li et al. (2003) conducted a comparison study in an attempt to correct InSAR measurements They assessed and compared the measurements of water vapor from radiosondes, GPS, and MODIS instruments MODIS overestimated PW against both the radiosonde and GPS measurements MODIS PW was greater than GPS PW with a scale factor of 1.09 ± 0.02 (standard devn’s on the order of 1-2 mm) As PW increased, MODIS tended to have an increasing + bias From Li et al. (2003)

12. MODIS data during Lili ~70 passes from September 1 through October 10, 2003 456 images covering different parts of the study area Typically 80-100% retrieval rate for NIR Typically 20-50% retrieval rate for IR

13. MODIS precipitable water MODIS IR 50% retrieval rate MODIS NIR 85% retrieval rate Day 248 2002, one month before Lili

14. GPS data Nearly three dozen GPS sites are operating along the south eastern coast of the U.S NOAA-FSL automatically provides derived PW data from many of these sites. We processed data from 10 IGS sites, 12 CORS (NOAA) sites, and 5 sites in the Caribbean and Central America.

15. The GPS signals are delayed as they pass through the atmosphere because the density of the atmosphere (which depends on pressure, temperature, and water vapor) changes the index of refraction. Source ??? GPS data processing Of note: P o not available at Caribbean and S. American sites

16. Isadore Lili

17. Tracks of Isidore and Lili

18. ZTD processed for 26 sites Gulf States Caribbean Islands Central America

19. GPS ZTD comparison Our GPS processing results were compared to those obtained from NOAA-FSL for six common sites. Statistics of the comparison (for example site MIA3) showed standard deviation of 11 mm ZTD and mean of 0 mm ZTD (implies std dev of 2 mm PW)

20. GPS ZTD data quality Maximum differences between ZTD values occasionally reached the order of 7 cm, indicating occasional discrete quality problems that will require investigation.

21. MODIS / GPS data comparison Modis data are reliably flagged as affected by clouds, where retrieved integrated water vapor includes only atmosphere above reflecting cloud tops. Mean MODIS – GPS = -0.16 cm PW4% Std dev MODIS – GPS= 0.26 cm PW6% RMS MODIS-GPS= 0.31 cm PW7%

22. Good comparison except for Miami Lili Oct 3 Isidore Sep 26

23. Conclusions Up to the point where clouds from the hurricane interfere with application of the NIR retrieval technique, MODIS provides high quality data. The accuracy, as measured in comparison to GPS, 7%, is slightly better than the expected 10% (Li et al, 2001, Gau and Kaufmann, 2003) Li et al, 2001 found MODIS overestimated PW by 7-14% where we found it underestimated relative to GPS The advantage of temporal resolution in GPS compared to MODIS may be important for the time scales of changes observed in a rapidly intensifying case such as Lili.

24. Acknowledgements NASA GRANT NRA-03-OES-02 Shu-Hua Chen –UC Davis Dennis Shea –NCAR Seth Gutman and Kirk Holub –NOAA-FSL