Institute of Meteorology and Water Management

2. Institute of Meteorology and Water Management „Satellite Remote Sensing as a tool for monitoring of climate and environment Piotr Struzik Satellite Research Department, IMWM Kraków

3. Presentation outline • Evolution of meteorological satellite system • Parameters related to climate derived from satellite informatiom • Benefits and limitation of satellite data for climatology. • Conclusions

4. Meteorological observations – ground obs., ships, aircrafts.

5. Development of meteorological satellite system

6. 1960 1978 1990

7. Global system of meteorological satellites – present

8. Clouds viewed from polar orbiting TIROS launched 1 Apr 1960

9. METEOSAT-8 GOES-E GOES-W Images from 5 geostacjonary satellites METEOSAT-5 MTSAT

10. Essential Climate Variables available from satellite observations

11. Key Areas of Uncertainty in Understanding Climate & Global Change * Earth’s radiation balance and the influence of clouds on radiation and the hydrologic cycle * Oceanic productivity, circulation and air-sea exchange * Transformation of greenhouse gases in the lower atmosphere, with emphasis on the carbon cycle * Changes in land use, land cover and primary productivity, including deforestation * Sea level variability and impacts of ice sheet volume * Chemistry of the middle and upper stratosphere, including sources and sinks of stratospheric ozone * Volcanic eruptions and their role in climate change

12. Satellite based Climate Data Records unique challenges: • the need to manage extremely large volumes of data; • restrictions of spatial sampling and resolution; • accounting for orbit drift and sensor degradation over time; • temporal sampling; • difficulty of calibrating after launch (e.g., vicarious or onboard calibration); • the need for significant computational resources for reprocessing.

13. Where satellite sensors can be placed on this diagram?

14. ATMOSPHERE TEMPERATURE SOUNDING • In 1969 Nimbus 3 carried the first of a new class of remote-soundingsensors, the Space Infra-Red Sounder (SIRS A), • First operational sounder system in 1972, the Vertical TemperatureProfile Radiometer (VTPR), aboard the NOAA 2 In 1978, • Next generation (TIROS N) waslaunched with an improved 20-channel High Infrared Sounder (HIRS)accompanied by the Microwave Sounder Unit (MSU) and Stratospheric • Sounder Unit (SSU) forming the TIROS Operation Vertical Sounder (TOVS) • In 2002 NASA launched Aqua carrying the first hyperspectralAtmospheric Infrared Sounder (AIRS)/AMSU/Humidity Sounder for Brazil (HSB) • 2006 – first METOP satellitewith IASI (8500 channels)

15. AIRS 2378 IASI 8461 HIRS 19 CrIS 1400

16. AIRS radiance changes (in deg K) to atm & sfc changes

17. SATELLITE PRECIPITATION

18. EARTH RADIATION BUDGET AND CLOUDS

19. Validation: Solar at TOA: CERES vs. ISCCP (B.Carlson, NASA)

20. CMa - verification Distribution close to normal, a bit higher cloudiness from satellite.

21. Mean cloudiness in June 2006 derived from CMa MSG product

22. VEGETATION DYNAMICS AND LAND COVER Vegetation index monthly anomaly time seriesJuly 1981 to December 2000. The impact of satellite drift is clearly noticeable, especially in the case of NOAA 11 and 14. Likewise, the impact of the Mt. Pinatubo eruption in June 1991 and El Chichon in March 1982 is also discernable.

23. Northern Latitude Greening Trends AVHRR observations suggest that the growing season increased between 1981 and 1994 (10%), but questions remain, mainly with respect to calibration and inter-calibration of sequential satellite instruments (Knyazikhin, Myneni, and Shabanov) Greening trend? Orbital drift? Inter-sensor variation? Noise in the channel data?

24. SNOW MAP PRODUCT September 2003 sea ice concentration SH. 12-month running anomalies of hemispheric snow extent, plotted on the seventh month of a given interval. Anomalies are calculatedfrom NOAA snow maps. Monthly anomalies are color coded by season: fall: orange; winter: blue; spring: green; summer: red.

25. Physicaland biological changes in the surface of the oceans on local, regional and basin scales. Oceans cover 70% of the earth surface, play a majorrole in the spatial and temporal distribution of weather patterns, the production of naturalresources, and the large-scale transport and storage of greenhouse gases.

26. Ozone monitoring by satellites Total Ozone Integrated Profile Ozone

27. Difficulties in use of satellite data for climate observations

28. A chronic difficulty in creating a continuous, consistent climate recordfrom satellite observations alone is that satellites and instruments have afinite lifetime of a few years and have to be replaced, and their orbits are not stable. Pre-launch calibration Post-launch vicarious calibration Intercalibration

29. Drift of orbital parameters

30. Comparison of albedo measurements with and without vicarious calibration. Without proper postlaunch calibration, spurious trends in the data can occur. SOURCE: Rao and Chen, 1995.

32. Differences in spectral characteristics vs. Long term vegetation monitoring

33. Annual mean anomalies of global average temperature (1979-2002) for the lower tropospherefrom satellites (T2) and for the surface. The surface temperature trend is +0.20 ± 0.06°C decade–1. The linear trend through 2002 for the UAH T2 product is 0.03 ± 0.09°C decade–1 The linear trend through 2002 for theRSS 0.11 ± 0.09°C decade–1. University of Alabama Huntsville (UAH) 5.1 (Christy et al., 2003) Remote Sensing System (RSS) (Mears et al., 2003).

34. Conclusions Satellite data offer an unprecedented potential for climate research provided that separate sensor/satellite dataare integrated into high-quality, globally-integrated climate products. Main issues are accuracy and stability of satellite measurements. Requirement for much improved calibration of satellite instruments, and intercalibration of similar instruments flying on different satellites. Data management – huge volume of satellite data. Future missions – new sensors / continuity of observations.