1. WP 8: Impact on Satellite Retrievals University of l’Aquila (DFUA [12]) Ecole Polytechnique (EPFL [13]) Observatory of Neuchatel (ON [14]) Partners (according to Contract): Meteorol. Inst. Munich (MIM [17]): Matthias Wiegner

2. Overview over Presentation 1. EARLINET-Contract: Workpackage 8 2. Relevance of WP 8 3. Contributions to WP 8 Definition Examples 4. Conclusions

3. EARLINET-Contract: 1. Quantify the sensitivity of radiances at the top of the atmosphere (toa) to variations of the aerosol distribution [...]. This will be used to provide an estimate of the impact of aerosols on retrievals [...] from spaceborne platforms. 2. Provide aerosol distributions for calibration purposes upon request [...]. Contract: Objectives and input of WP8

4. Contract: Description of work This is done by running adequate radiative transfer models using the aerosol data [...]. As a result, inversion algorithms [...] can be critically reviewed and improved. Additional lidar measurements [...] will be performed at special occasions when satellite overpasses close to an EARLINET station occurs [...]. For this part to stay within the limits of the available resources it will be done only on request.

5. Relevance of WP 8 multispectral and multiangular radiances from satellites used to retrieve aerosol optical depth critical over land surfaces (albedo, orography) complex retrieval algorithms require validation „Validation of atmospheric parameters“

6. Relevance of WP 8 multispectral and multiangular radiances from satellites used to retrieve surface properties (e.g. precision farming) determine atmospheric influence (unknown aerosol effect) corrections of atmospheric masking require input and validation „Validation of surface parameters“

7. Relevance of WP 8 Radiative transfer calculations required to understand satellite data aerosol distribution is one controlling parameter contribution of lidar data to be assessed „Improvement of aerosol understanding“

8. Three contributions to WP 8 Demonstrate the benefit of lidar data on the basis of dedicated experiments Note: WP‘s ordered by „time allocated“: WP8 is 15. out of 20. Offer our datasets to the satellite community for validation purposes Identify cases where lidar data are useful

9. First contribution Actions proposed: Supply survey of available aerosol extinction profiles (site, time, wavelength) Goal: Support validation of satellite retrievals by supplying lidar data (possible candidates: Envisat, MSG community) Data dissemination: On request (Webpage)

10. First contribution Results/Conclusions: Aerosol extinction profiles from more than 20 lidar stations, two times a week and for more than two years, are available. Validation of aerosol retrievals requires a careful selection of time and place, and averaging over reasonable periods. Envisat and MSG are still at the beginning of their operation times. Final success requires extra funding (also for the satellite community), time horizon: 2003/04 “Seed is set, but harvesting takes time”

11. Three contributions to WP 8 Demonstrate the benefit of lidar data on the basis of dedicated experiments Note: WP‘s ordered by „time allocated“: WP8 is 15. out of 20. Offer our datasets to the satellite community for validation purposes Identify cases where lidar data are useful

12. Acquisition mode: CHRIS: 18 km swath, 25 m resolution, 19 spectral bands, along track (5 angles) Second contribution Time and Place: May, June, July and August 2002 in Gilching In co-operation with: Goal: Full characterization of surface and atmosphere of exactly the same scene (for calibration of satellite sensor and algorithms) Requirements: co-incidence and co-location and very small satellite pixel required.

13. Second contribution Results/Conclusions: Satellite PROBA encountered severe problems: no data are available up to now. First data are announced for fall this year. A new special field campaign is difficult to be organised.

14. Three contributions to WP 8 Demonstrate the benefit of lidar data on the basis of dedicated experiments Note: WP‘s ordered by „time allocated“: WP8 is 15. out of 20. Offer our datasets to the satellite community for validation purposes Identify cases where lidar data are useful

15. Third contribution Actions: Performing model calculations with realistic aerosol extinction profiles to investigate the influence of aerosols on toa-radiances Goal: Support model development by supplying lidar data

16. Variation of aerosol optical depth Variation of aerosol type Variation of aerosol (vertical) distribution Variation of surface albedo Variation of solar zenith angle Fixed wavelength (532 nm) Radiative transfer calculations

17. Vertical aerosol distribution: 5 cases (1) (2) (3) (4) (5) Model calculations

18. Normalized to isotropic radiance „Anisotropy-Function“Anisotropy-Function Radiances at top of atmosphere

19. as a function of surface albedo for different aerosol optical depths fixed aerosol type, aerosol profile and solar zenith angle Radiance/flux at toa

20. different aerosol type Radiance/flux at toa

21. different aerosol type

22. Radiance/flux at toa different aerosol type

23. Radiance/flux at toa different aerosol type

24. Radiance/flux at toa same as before: 32.5 0

25. Radiance/flux at toa now: 62.5 0

26. Radiance/flux at toa as a function of surface albedo for different aerosol types fixed optical depth, aerosol profile and solar zenith angle

27. Radiance/flux at toa Different optical depth

28. Radiance/flux at toa Different optical depth

29. Radiance/flux at toa Different optical depth

30. Radiance/flux at toa Different optical depth

31. Radiance/flux at toa as a function of surface albedo for different aerosol profiles fixed optical depth, aerosol type and solar zenith angle

32. Radiance/flux at toa Different aerosol type

33. Radiance/flux at toa Different aerosol type

34. Radiance/flux at toa Different aerosol type

35. Radiance/flux at toa Different aerosol type

36. Radiance/flux at toa as a function of surface albedo for different aerosol mixtures fixed optical depth, aerosol types and solar zenith angle

37. Radiance/flux at toa Different aerosol type

38. Radiance/flux at toa Different aerosol type

39. Radiance/flux at toa Different aerosol type

40. Radiance/flux at toa Different aerosol type

41. Radiance/flux at toa Different layer width

42. Conclusions from the model simulations Satellite radiances are significantly influenced by aerosols: -- optical depth -- aerosol type -- aerosol profile

43. Conclusions from WP 8 Validation campaigns of aerosol parameters with lidar data require extra efforts Model simulations show that the aerosol vertical distribution is a second order effect for satellite remote sensing, but should be provided together with a aerosol classification („aerosol type“)

44. Th a nk y o u for l i s te ning

45. The goal of Workpackage No. 8 includes the modeling of the aerosol influence on radiances measured by satellites and the provision of additional lidar measurements on request. What does this mean? Measurements: Lidar data are available since May 2000. Dedicated measurements simultaneous to satellite overpasses make sense if pixel are small and cloud free conditions can be guaranteed. On the other hand, the existing data base can be used for validation of satellite measurements and their products. Model calculation: Models for atmospheric corrections (e.g., to retrieve surface properties) and models to derive aerosol properties can be supported by supplying lidar data. Remark: The development of such models itself is beyond the scope of EARLINET. Both “classes” are linked and cannot be considered separately. Goals of the Work-Package

46. Small but relevant Workpackage Satellite provide global coverage but vertical resolution is poor. Aerosols are hard to be detected by passive radiometers, thus Validation and additional data are useful. Aerosols influence retrievals of geophysical and atmospheric parameters Global climate models will benefit of high resolved aerosol data as Well as (conventional) dedicated aerosol missions

47. EARLINET and Satellites General remarks: Meteorological satellites suitable for aerosol remote sensing require “good” spatial and spectral resolution. For that reason, SeaWIFs is presently the most promising candidate. Geostationary satellites have poor radiometric accuracy and spectral resolution, GOME et al. have very poor spatial resolution, Landsat et al. have very poor temporal sampling, and sensors with very high spatial resolution are not yet in orbit (MERIS [250 m], Chris et al. [25 m]). Thus, we follow two options: Option 1: plan dedicated experiments on the “compare same atmospheric volume”-concept [risk: overcast conditions] and Option 2: select data sets already available on the “validate aerosol parameters”-concept

48. Option 2: Aerosol Validation Output: Several calibration points for the map of aerosol optical depth derived from (e.g.) v. Hoyningen-Huene’s SeaWIFs retrieval. Information of special aerosol stratifications that might help to explain possible deviations. E.g., check, whether algorithm works in the presence of Saharan dust layers. Provision of information of the aerosol type (if possible, e.g., from trajectories, lidar data themselves, auxiliary data) to support satellite retrieval algorithm (input for them). Possible co-operation with University of Bremen (v. Hoyningen-Huene)

49. Option 2: Aerosol Validation (contd.) Background Information: A SeaWIFs algorithm to derive aerosol optical depth exists and has been (successfully) applied. SeaWIFS has a spatial resolution of about 1 km and a coverage of 1800 km (swath width); similar to AVHRR Algorithm works best in the spectral range between 412 - 510 nm (surface is dark); lidar data of 532 nm can be extrapolated. Times to be compared should be in spring and early summer (green vegetation; no problems with water stress) MERIS will have a better resolution but will be available not before spring 2002. Sciamachy has a very poor spatial resolution.

50. Option 2: Aerosol Validation (contd.) To be Discussed: Data from stations not directly involved in this work package would be required. Is that possible? Who will calculate the optical depth from the extinction profiles (owner or M.W.)? Is an extra qualitity check required/desired by the owner of the data? Selection of episodes from the diurnal cycle subset (best time of the day is 11-13 hours)? How many episodes should be selected (one, two, more?) Should we include algorithms to derive aerosol optical depth over land from other institutes (answer from Berlin is pending)?

51. The goal of Workpackage No. 8 includes the modeling of the aerosol influence on radiances measured by satellites and the provision of additional lidar measurements on request. What does this mean? Measurements: Lidar data are available since May 2000. Dedicated measurements simultaneous to satellite overpasses make sense if pixel are small and cloud free conditions can be guaranteed. On the other hand, the existing data base can be used for validation of satellite measurements and their products. Model calculation: Models for atmospheric corrections (e.g., to retrieve surface properties) and models to derive aerosol properties can be supported by supplying lidar data. Remark: The development of such models itself is beyond the scope of EARLINET. Both “classes” are linked and cannot be considered separately. Goals of the Work-Package

52. Deliverables April 2002: Report on aerosol impact on satellite retrievals Next steps of WP 8 Start: May 2000 End: December 2002 Other Deadlines May 2002: Contribution to Annual Report