Tropical Cyclone Analysis With Satellite Radars

1. Tropical Cyclone Analysis With Satellite Radars SOES 6026 – Radar Remote Sensing Ray Bell

2. Tropical cyclones • Applications • Scatterometers • Altimeters • SARs • Forecasting • Conclusions

3. Applications • Influence 10,000s people every year and can shape financial markets. • Remove heat and moisture from the ocean. • Influence levels of phytoplankton by upwelling nutrients. • Strong gas exchange between the air and ocean. • High wind speed events >20m/s

4. Scatterometers • Send out radar signal obliquely and measure σ0 • Wind speed and direction from different azimuth directions – GMF • Spatial resolution 25-50km2, swathwidth of 1800km for QuikSCAT, repeat cycle of ~4 days

5. Scatterometers QuikSCAT wind speeds and direction of hurricane Katrina in 2005. white barbs show heavy rainfall. NASA (2006). However, winds measured to be >140 knots (70 m/s) at the time, much larger than the scatterometer measures

6. Scatterometers – Extreme winds • QSCAT-1 GMF limited at 30 m/s (Hennonet al, 2006). Cyclone winds speeds much stronger . • σ0 become saturated (Weissman et al, 2002; Yuan, 2004) • Improved GMFs – parametric equations for C and Ku bands. Can obtain winds speeds up to 65 m/s Fernandez et al (2006). • Still not quite large enough for some extreme events and are also limited near the eye... H*Wind vs. Retrievals of empirically tuned wind speeds in the Ku-2001 GMF. It is also post-processed to be a 2.5 km Ultra High Resolution product (UHR KU) Hennonet al (2006)

7. Scatterometers – Rain • Rain affects small scale roughness, attenuation and scattering of the radar signal in the atmosphere (Weissmanet al, 2002) • Biggest limitation of the radar signal in tropical cyclones – hinders observations of any wind speeds. • Nie and Long (2008) created a simultaneous wind/rain retrieval (SWRR) using the C-band with the ERS scatterometer. • Improve wind velocity estimates and the surface rain rate in moderate to heavy rain cases. • Results become noisier

8. Altimeters • Better spatial resolution than Scatterometers ~5km. (-) Nadir direction • (-) Longer repeat cycle • Measure shape of the waveform to obtain wind speed • Uniquely observe tropical cyclones with Hs and SSHa

9. Altimeters Combined sensor output for a single Envisat pass across Hurricane Juan black lines indicating the nadir track. (middle) The derived attenuation from the RA-2 (in black when statistically significant). Quartly and Guymer(2007)

10. Altimeters • Most research investigate the affect of high wind speeds and heavy rain on the altimeter wave forms in tropical cyclones (Young, 1993; Quartleyet al, 2007). • Hs – Quilfen et al (2006) showed that Hs reached up to 11m and 14.7m either side of the centre of Tropical cyclone Isabel by using its own tracking algorithm to process C-band waveforms little affected by rain (Quartly, 1999). • Validate the theory that high sea states and wind speeds are larger to the right of the direction of the tropical cyclone (Willoughby and Rahn, 2004)

11. Altimeters - Hs Hurricane Isabel in 2003 best track as determined by the Hurricane Research Division, and the two Jason orbits J50 and J152. Number on the track are maximum wind speeds. Circles are where the hurricane located when Jason-1 flew over. Quilfen et al (2006)

12. Altimeters - Hs Jason Orbit 50 Jason Orbit 152 Latitude where centre of hurricane was located

13. Altimeters - SSHa • SSHa can be used to quantify the integrated water column temperature. • Cyclogenesis - SST > 26°C. • Anomalous warm eddies can intensify tropical cyclones and influence their tracks (Goniet al, 2005) Super typhoon Maemi Western North Pacific, 200. T/P and Jason-1 composite during one weeks cycle (30 Aug – 8 Sep). Colour shows intensity and circle radius of maximum winds. Lin et al (2005)

14. SARs Envisat ASAR image for Hurricane Rita in 2005. Results not clear, near range Shenet al (2009)

15. SARs • Simulate a SAR image with the Holland model (1980), look at an actual SAR image and compared with HRD analysis winds (Shenet al, 2009). • Improves accuracy of the radius of maximum hurricane winds. (Left) Simulated SAR image based on the HRD wind, and (Right) the final retrieved wind speed with application of the speed ambiguity removal method.

16. Tropical cyclone forecasting • (me in 3/4 years time!!!) • The coherent spatial coverage and high spatial resolution by some radar’s give strong implications for modelling. • Location, intensity and frequency • Radars provide additional data. Sample areas with few in-situ measurements e.g. Southern hemisphere. • Satellites provide high spatial resolution results where as some storm models have previously been limited with resolution (Kuriharaet al, 1990)

17. Tropical cyclone forecasting Sea level pressure analysis (hPa) with QuikSCAT winds superimposed. Much improved location in the QuikSCAT case. Atlas et al (2005)

18. Tropical cyclone forecasting • No extreme winds but QuikSCAT can give the distance at which winds of various speeds extend from the storm centre – critical information in emergency management. • High resolution products can obtain help locate the storm centre (Said and Long, 2008) – but rain often causes problems and noisier. • Validation and tuning of the models. • ECMWF models assimilate altimeter winds

19. Conclusions • SARs offer potential of obtaining high spatial resolution results • (-) Hard to utilize the winds • Altimeters offer poor spatial coverage. Uniquely sample Hs and SSHa • Scatterometers provide good detail on wind direction and wind speeds around the tropical cyclone • (-) Poor results in the core region – high winds and rain • Synergy of all radars • Improve observations, forecasts and knowledge even further

20. Future work • Radars are limited in obtaining results as large amount of foam, sea spray and wave breaking occurs and distorts the radar signal (Yang et al, 2008). This is potential for future work. • Extended Ocean Vector Wind Mission – scatterometer • C-band pencil beams cover the wind speed range typical of tropical cyclones and mitigate rain contamination • X-band pencil beam radiometer for better rain corrections. (Gaston and Rodríguez, 2008). • Further investigate rain errors

21. Any questions ??? References • Atlas, R., Hou, A.Y. and Reale, O. (2005) Applications of SeaWinds scatterometer and TMI-SSM/I rain rates to hurricane analysis and forecasting. Journal of Photogrammetry & Remote Sensing, 59. pp. 233-243. • Fernandez, D. E., Carswell, J., Frasier, S., Chang, P. S., Black P. G. and Marks, F. D. (2006) Dual-polarized C and Ku-Band ocean backscatter response to hurricane force winds. Journal of Geophysical Research, 11, C08013, • Goni, G J., Black, P. and Trinanes, J. (2003) Using satellite altimetry to identify regions of hurricane intensification. AVISO Newsletter, No. 9, CNES, Paris, France, 19–20. • Hennon , C. C., Long, D.G. And Wentz, F.J. (2006) Validation of QuikSCAT wind retrievals in tropical cyclone environments. 27th Conference on Hurricanes and Tropical Meteorology, Monterey, CA, American Meteorological Society, JP1.1 • Kurihara, Y.M., Bender, A., Tuleya, R.E., Ross, R. (1990) Prediction experiments of hurricane Gloria (1985) using a multiply nested movable mesh model. Monthly Weather Review. 118(10), pp. 2185– 2198. • NASA (2006) Scatterometer image. Available online from: http://visibleearth.nasa.gov/view_rec.php?id=20206. Accessed 3rd May 2010 . • Nie, C. and Long, D.G. (2008) A C-band Scatterometer Simultaneous Wind/Rain Retrieval Method. IEEE Transactions on Geoscience and Remote Sensing, 46(11). Pp. 3618-3632. • Quartley, G. D. and Guymer, T.H. (2007) Realizing Envisat’s potential for rain cloud studies. Geophysical Research Letters. 38, L09807. doi:10.1029/2006GL028996

22. Any questions ??? References • Quilfen, Y., Tournadre, J. and Chapron, B. (2006) Altimeter dual-frequency observations of surface winds, waves, and rain rate in tropical cyclone Isabel. Journal of Geophysical Research, 111, CO1004. doi:10.1029/2005JC003068 • Said, F., and Long, D.G. (2008) Effectiveness of QuikSCAT's ultra high resolution images in determining tropical storm eye location. Proc. of the International Geoscience and Remote Sensing Symposium, Boston, MA, IEEE, 351-354. • Shen, H., He, Y. and Perrie, W. (2009) Speed ambiquity in hurricane wind retrieval from SAR imagery. International Journal of Remote Sensing. 30(11), pp. 2827-2836. • Weissman, D.E., Bourassa, M. A. and Tongue, J. (2002) Effects of rain rate and wind magnitude on Sea Winds scatterometer wind speed errors. Journal of Atmospheric and. Oceanic Technology., 19, pp. 738-746. • Willoughby, H. E. and Rahn, M. E. (2004) Parametric representation of the primary hurricane vortex. Part I: Observations and evaluation of the Holland (1980) model. Monthly Weather Review, 132, pp. 3033-3045. • Young, I.R, (1993) An estimate of the Geosat altimeter wind speed algorithm at high wind speeds. Journal of Geophysical Research. 98(C11), pp. 22,275-20,285. • Yuan, X. (2004) High-wind-speed evaluation in the Southern Ocean. Journal of Geophysical Research, 109, D13101, doi:10.1029/2003JD004179.