1. The use of satellite data in marine aerosol studies: future perspectives, challenges, development needs Gerrit de Leeuw Finnish Meteorological Institute & University of Helsinki ” a bit of thinking aloud”

2. Oceanflux Sea Spray Aerosol: achievements Satellite data used: Wave height Ocean Colour (OC) Aerosol and cloud properties (several instruments) (SST) (Wind info) Development improved sea spray source function parameterized in terms of Reynolds number Re Hw ; incudes effects of: Wind speed and history Wave state SST Salinity 5 lognormal modes Size range: 3 nm – 6 µm dry diam. Wind speed range: 3-26 ms -1 Effects of organics accounted for Implementation in climate model: ECHAM-HAM + SALSA Aerosol load (AOD) Direct radiative effect Indirect radiative effect Publications: Sea Spray Source Function, Ovadnevaite et al., ACP 2014 Climate Modeling & Radiative effects: Partanen et al., ACP 2014

3. Climate effects of sea spray aerosol Direct effect of sea salt aerosol: global mean -0.5 W m -2 (cooling) Indirect effect of sea salt aerosol: (+0.3 W m -2 ) (warming) Large sea salt particles act as condensation sink for sulfate; decrease nucleation and condensational growth of sulfate particles; decrease maximum supersaturation in clouds. Partanen et al., ACP 2014

4. OSSA achievements and satellites (1) The Mace Head data sub-set used to derive the OSSA source function (Ovadnevaite e tal. ) was available because of the long time series (decades) which makes it possible to find such events The results from this event (fluxes) match very well with direct eddy correlation measurements during the SOLAS SEASAW cruise on the open North Atlantic (Norris et al.) These two data sets, both in situ, were used together to span the full size range (3 nm – 6 µm dry diam.) Satellite data were used in the OSSA study to provide drivers used in the parameterizations and for comparison with model results Satellite data have proven their usefullness in SSA production and effects : Can they be used in other studies? How? And for other purposes?

5. OSSA achievements and satellites (2)  Satellites also provide multi-decadal and global observations of aerosol and driving parameters:  Less accurate than in situ  Less detailed than in situ  But consistent (for same instrument)  We need relaible AOD data over ocean:  Current uncertainties, as determined by the error envelope or uncertainty estimates, are better than over land.  Is this good enough?  Can we expect further improvement?  What can we do with current data, accepting their uncertainties  Contradiction data sets and no decisive arguments on what is better

6. W-fraction Toth et al., JGR 2013 W fraction satelite: Albert et al., in prep.

7. OSSA achievements and satellites (3) Questions: 1. Can satellite long-term global time series be used in SSA studies to:  Identify special cases or events? (statistics, pdfs, …)  Develop climatologies  Direct from satellites (multi-year observations, e.g. CALIOP aerosol layer height)  As drivers to derive climatologies (e.g. SSSF from wind speed or wave height or …)  Detection or evaluation of trends  Constrain models  Evaluate emissions 2. Individual measurements or short time series:  Case studies 3. What are current and future needs from satellites? 4. Use Past, Current and Future satellite data (as appropriate)!

8. CALIOP AOD Winker et al, 2013: Fig. 3. Mean 532 nm AOD, January 2007– December 2011: (a) cloud-free, daytime; (b) cloud-free, nighttime; (c) all-sky, daytime; (d) all-sky, nighttime. 1. We don’t see the high AOD band in the Southern Ocean, observed by some other satellites, some model experiments, but it’s absence is confirmed by MAN: Who is right? 2. What is the AOD wind speed dependence? Does it depend on location through other parameters (e.g. SST?) Can CALIOP help?

9. CALIOP Aerosol layer height Winker et al. (2013): Fig. 11. Regional zonal aerosol extinction (km−1), 2008: (a) 180–135◦ W, MAM; (b) 75–40◦ W, JJA; (c) 15◦ W–30◦ E, JJA; (d) 70–90◦ E, JJA. CALIOP provides AOD, aerosol typing, vertical structure; cloud free: Can layer height and AOD together with typing be used to say something about SSA production?

10. Flux parameterization: the OSSA source function i ii CMD i F i (R Hw ) 11.370.024.58*(R Hw -1e 5 ) 0.556 21.50.0480.0045*(R Hw -1e 5 ) 1.08 31.420.10233.05*(R Hw -1e 5 ) 0.545 41.530.2791.3*(R Hw -1e 5 ) 0.79 51.851.0351.02*(R Hw -2e 5 ) 0.87 Oceanflux Workshop, Brest, France; 24-29Sep2013 Does this provides a means to determine an SSA production flux using satellite retrieved wind speed, H s and SST?

11. Oceanflux Sea Spray Aerosol: open questions Quantitative effects of organic matter (OM) on: Hygroscopic growth Optical properties Cloud condensation nuclei Current OM parameterizations largely based on Mace Head data: extend to other oceans by using satellite data: Combine model data and satellite observations to determine aerosol & cloud properties, based on current knowledge Evaluate over North Atlantic using satellite data: ATSR, MODIS, PARASOL, CALIOP (+future satellites S3, S4, S5, Earthcare) provide info on aerosol properties and vertical distribution How well does that work on global oceans, implications?

12. SSA: Sea Salt + Organic Matter Sub-micron SSA enriched in OM Fine mode SSA enriched in OM has low hygroscopicity: How does that affect optical properties? Is there a correlation between FM marine aerosol, especially in ’clean’ over ocean areas, and Ocean Colour (OC)? Are there any correlations between FM AOD, OC, SST, WSPD, H s ?

13. Effect of SST Jaegle: comparison model and satellite OAD OSSA SSSF: Re Hw due to implicit dependence on viscosity Mårtensson 2003 and Zabori 2012 are laboratory experiments Salter et al., OSSA workshop 2013 Zabori et al., 2012 23 15 5 -2 What causes the differences, esp at SST<10 o C? Can large satellite data sets help?

14. AOD wind speed dependence The problem is still not resolved: what can satellite observations contribute? In this figure several satellite data sets are already inclujded: MODIS, CALIOP, AATSR, …. Which area? Is the N Atlantic different from other oceanic regions? Other effects than wind speed? What can satellite data combined with models contribute? Smirnov et al., AMT 2012

15. Whitecaps Whitecap fraction W determined from radiometer data differs signifincantly from that determined from visual observations. Furthermore, there is strong frequency dependence as a consequence of penetration depth Radiometer-determined W has a quadratic depnedence on wind speed with a very high correlation coefficient which leaves very little room for other drivers such as SST Monique Albert et al., 2015, in preparation

16. Conclusions OSSA has made good use of satellite data Satellite data (OC) are crucial in studies on the enrichment of SSA in organic matter Satelites provide a global data set, with time resolution varying from daily to weekly on aerosols (AOD) and environmental driver which infleunce the production, transport an removal of aerosol particles, as well as on cloud properties. Hence in a very short time an extensive data set could be obtained on SSA and ambinet parameters, from different (types of) instruments, the potential of which should be epxlored to obtain a better understanding of the life cycle of SSA, including effects of OM, and their influence on cloud properties. A possible approach could be the statistical analysis of a multi-year data set ove selected oceanic areas But on the other hand, a data set could be analyzed which covers a wide range of ambient (oceanographic or atmosheric) parameters Look for new and chalenging instruments, but don’t forget the existing data sets

17. 17 ESA UNCLASSIFIED - For Official Use

19. http://globwave.ifremer.fr/products/globwave- satellite-data/altimeter-l2p-data

20. Use of satelites in OSSA SSA Source Function development (Ovadnevaite et al., 2014): Wave height constrains ECMWF WAM model, which was used instead of sparse satelite data because of limited field data sets Wave height can be used with OSSA source function in further studies, as well as other satellite data used in the parameterization Effects of Organic matter Ocean Colour (globcolour, future OC-CCI) data used to determine OM fraction is source function Implemented in climate model (Partanen et al., 2014) Model evaluation: Satellite aerosol and cloud properties OSSA Workshop, Galway, 30.9 & 1.10, 2013