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Satellite Climatologies/ Satellite Composites

Satellite Climatologies/ Satellite Composites. Dr. Bernadette Connell CIRA/CSU/RAMMT March 2005. Outline. Introduction Motivation on the Global Scale Motivation on the Regional Scale Types of Cloud Composites and Examples Concluding remarks Comments on the Lab. Introduction.

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Satellite Climatologies/ Satellite Composites

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  1. Satellite Climatologies/Satellite Composites Dr. Bernadette Connell CIRA/CSU/RAMMT March 2005

  2. Outline • Introduction • Motivation on the Global Scale • Motivation on the Regional Scale • Types of Cloud Composites and Examples • Concluding remarks • Comments on the Lab

  3. Introduction Satellite Climatologies: a relatively new climatological tool. • First composites developed in the 1960’s. Cloud Composites are the most popular Other Composites include: fire, drought, snow cover, ice cover, and sea surface temperature.

  4. Motivation on the Global Scale • Climate modeling and climate monitoring: * global distribution of clouds * cloud properties * diurnal, seasonal, and interannual variations • International Satellite Cloud Climatology Project (ISCCP) (Schiffer 1982, Schiffer and Rossow 1983) • Uses imagery from Geostationary and Polar Orbiting satellites • Coarse resolution (280 km analysis grid) • CIRA: Prof. Tom Vonder Haar, Dr. Garrett Campbell

  5. Motivation on the Global Scale • What is global distribution of water vapor? • National Aeronautics and Space Administration Water Vapor Project (NVAP) (Randel et al. 1996) • Combines information from TOVS, SSMI, and radiosonde observations • 8-yr (1988-1995), 1o X 1o spatial resolution • Principal Investigators at CSU/CIRA: Prof. Tom Vonder Haar, Dr. Dave Randel and Prof. Graeme Stephens.

  6. Motivation on the Regional Scale • Satellite data supplement surface based measurements in determining cloud cover and cloud frequency. • Satellite composites show the diurnal cycle of cloudiness in relation to geographic features (water/land changes, topography). • Precipitation estimates can be made to supplement data sparse regions.

  7. Motivation on the Regional Scale • The composited information can be used as a training product for new forecasters. • Provides higher resolution information for climate modeling purposes.

  8. Types of Cloud Composites Visible, WV (6.7 um), IR (10.7 um), Fog product, combined image products. • Qualitative: Image averaging, maximum and minimum composites. • Quantitative: Cloud frequencies by threshold techniques • Composites on various time scales: Diurnal-Monthly, Monthly, Seasonal, Annual • Stratification by Regimes

  9. GOES-8 Visible average composite for July 1999 1615 UTC n=30

  10. GOES-8 Visible composite of maximum brightness count for July 1999 at 1615 UTC n=30

  11. GOES-8 IR4 (10.7 um) composite of coldest pixels for July 1999 at 1615 UTC n=30

  12. GOES-8 Visible composite of minimum brightness count for July 1999 at 1615 UTC n=30

  13. Types of Cloud Composites Visible, WV (6.7 um), IR (10.7 um), Fog product, combined image products. • Qualitative: Image averaging, maximum and minimum composites. • Quantitative: Cloud frequencies by threshold techniques • Composites on various time scales: Diurnal, Monthly, Seasonal, Annual • Stratification by Regimes

  14. GOES-8 Visible background image (similar to composite of minimum brightness counts) for July 1999 1615 UTC

  15. GOES-8 Visible image for July 5, 1999 at 1615 UTC

  16. Cloud – no cloud image for July 5 1999 at 1615 UTC

  17. GOES-8 Visible cloud frequency for July 1999 at 1615 UTC n=30

  18. GOES-8 IR4 (10.7 um) image with pixels colder than 283 K shaded blue – for July 5 1999 at 1615 UTC

  19. GOES-8 IR4 (10.7 um) cloud frequency for July 1999 at 1615 UTC Temperature threshold of 283 K. n=30

  20. Types of Cloud Composites Visible, WV (6.7 um), IR (10.7 um), Fog product, combined image products. • Qualitative: Image averaging, maximum and minimum composites. • Quantitative: Cloud frequencies by threshold techniques • Composites on various time scales: Diurnal-Monthly, Monthly, Seasonal, Annual • Stratification by Regimes

  21. Types of Cloud Composites • Visible, WV (6.7 um), IR (10.7 um), Fog product, combined image products. • Image averaging, maximum and minimum composites. • Cloud frequencies by threshold techniques • Composites on various time scales: Diurnal-Monthly, Monthly, Seasonal, Annual • Stratification by Regimes

  22. Regime Satellite Composites • Mr. Ken Gould, NWS, Tallahassee, Fl. in cooperation with CIRA, has developed Mesoscale Summer Sea-breeze composites (June, July, August 1996 -present. • Stratifies regimes by using a mean layer (1000 - 700 mb) vector wind incorporating onshore/offshore/parallel to shore flow and flow strength.

  23. Regime Composites • Shows preferred areas of convective development • Shows effects of synoptic flow changes • Shows effects of small scale features such as bays, lakes, and rivers • Gives insight to timing and amount of cloud development • Can be integrated with other mesoscale climatologies

  24. Tallahassee Summer Sea-breeze Composites Regime Description 1 Light and variable or light SE 2 Light to moderate (3 to 10 kts) E to NE 3 Strong (> 10 kts) E to NE 4 Light to moderate (3 to 10 kts) W to SW 5 Strong (> 10 kts) W to SW 6 Moderate (6 to 10 kts) Se to S 7 Strong (> 10 kts) SE to S 8 Light to moderate (3 to 10 kts) N to NW 9 Strong (> 10 kts) N to NW

  25. Regime 1

  26. Applications of Satellite Climatologies at the Tallahassee WFO • Short-Term Forecast (NOW) • Convective initiation • Timing of frontal passage • Zone Forecast • Accurate and detailed POPs • Zone groupings by regime • Severe/flood potential • Marine Forecast • Land breeze convection • Sea fog/stratus potential • Aviation Forecast • TAFS- ceilings and chance/timing of convection • TWEBS- cloud and convective coverage on route

  27. Agriculture and Forest Fire Frequency • Drier months in Costa Rica and surrounding countries: January - May • Composites of the experimental fire product

  28. Future Opportunities • Continue archival of imagery and the development of both Visible and 10.7 um cloud frequency composites. • Use multi-channel imagery to obtain satellite-based precipitation estimates. • Compare with other available information such as surface precipitation measurements and estimates from other satellite based measurements.

  29. References Connell, B. H., K. J. Gould, and J. F. W. Purdom, 2001: High resolution GOES-8 visible and infrared cloud frequency composites over northern Florida during the Summers 1996-1999. Wea. Forecasting, 16, 713-724. Connell, B. H., and K. J. Gould, 2000: GOES-8 Visible cloud frequency composites of the convectively active sea breeze under stratified synoptic flow over the Florida Panhandle. Tenth Conference on Satellite Meteorology and Oceanography. AMS, Boston, MA. Gould, K. J, and H. E. Fuelberg, 1996: The use of GOES-8 Imagery and RAMSDIS to develop a sea breeze climatology over the Florida Panhandle. Eighth Conference on Satellite Meteorology and Oceanography. AMS, Boston, MA. Klitch, M. A., J. F. Weaver, F. P. Kelly, and T. H. Vonder Haar, 1985: Convective cloud climatologies constructed from satellite imagery. Mon. Wea. Rev., 113, 326-337

  30. LAB • View IR4 threshhold temperature composite loops comparing June, July, and August over Central America • View Regime climatologies for Tallahassee.

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