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 1: === **S2S Aerosol sub-project** ===
 2: 
 3: 
 4: **Membership:**
 5: 
 6: Angela Benedetti (ECMWF, UK, Angela.Benedetti@ecmwf.int) (Main Contact)
 7: 
 8: Frederic Vitart ( ECMWF, UK, Frederic.Vitart@ecmwf.int )
 9: 
10: Ariane Frassoni Dos Santos (CPTEC, Brazil))
11: 
12: Francois Engelrecht (University of the Witwatersrand, South Africa)
13: 
14: Andrea Molod (NASA/GMAO, USA) (Liaison with the WRSWG-S2S)
15: 
16: 
17: ==== 1. Scientific Objectives ====
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19: 
20: The role of aerosols in the Earth's radiation balance has been investigated by the climate modeling community since the early 90s. However, in Numerical Weather Prediction, state-of-the-art operational models are still using climatology which can describe the average effect of aerosols on the radiative balance. This is due to the fact that there has been so far no definite proof that sophisticated aerosol schemes are needed and the cost of running a full integrated aerosol system at the high resolution of current NWP systems is considered at the moment prohibitive. As for NWP, all the operational S2S models contributing to the S2S database use climatological aerosols. However, recent studies suggest a strong modulation of aerosols by the Madden Julian Oscillation which is a major source of predictability in the Tropics at the sub-seasonal to seasonal time range and that the MJO-related intra-seasonal variance accounts for about 25% of the total AOT variance over the tropical Atlantic (Tian et al. 2011) primarily through its influence on the Atlantic low-level zonal winds.
21: 
22: The scientific objectives of our sub-project are: 1) Estimate the impact of prognostic (vs climatologically specified) aerosol loading in the atmosphere on S2S forecasts via its effects on radiation 2) Determine the level of complexity needed 3) Estimate the predictability of aerosols (e.g. dust) at the S2S time-scale, and 4) assess the value of these forecasts for applications
23: 
24: 
25: ==== 2. Proposed Activities for 2019-2023 (S2S Phase 2) ====
26: 
27: The major activity of this sub-project for the period 2019-2023 will be to perform coordinated S2S experiments to address the above scientific questions. These experiments will be coordinated with WGNE and GAW. In these experiments, the full score of an “active” simulation will include:
28: 
29: * Generation of aerosol abundance in the atmosphere from source regions (e.g. wind blowing over deserts, sea salt - more from storm regions)
30: * Precipitation scavenging and general gravitation fall out
31: * Advection between the two
32: * And then its impact is only on radiation
33: *  Several centres have already expressed a strong interest in participating: ECMWF, NCEP, NASA, CMA , JMA , KMA , CNRM and ECCC.
34: 
35: ==== 3. WGNE-S2S-GAW Aerosols Project (WGNE-S2S-GAW-Aer) ====
36: 
37: The WGNE-S2S-GAW Aerosols project (WGNE-S2S-GAW-Aer) includes two main components: one is built on WGNE-AerI by running higher resolution regional models in order to address the importance of interactive aerosols on weather predictability; the second component considers sub-seasonal reforecasts experiments based on ensemble approach in a global scale in order to address the importance of interactive aerosol on sub-seasonal predictability. The WGNE-S2S-GAW-Aer will benefit from the expertise of the Joint Working Group on Forecast Verification Research (JWGFVR)regarding the best metrics to be used to assess both NWP deterministic and ensemble forecasts, taking advices on what metrics to evaluate meteorological and air quality variables.
38: 
39: The protocol of WGNE-S2S-GAW-AER  has been finalized and is available [[here>>attach:WGNE_S2S_GAW_Aerosol_Project_2019.pdf]]. S2S is involved in the second set of experiments: extended-range re-forecasts with and without interactive aerosols (with direct or indirect effect) covering the period 2003-2019 (see protocol for more details).
40: 
41: * Participating centres: ECMWF, NCEP, NASA, CMA , JMA , KMA . Possibly CNRM and ECCC.
42: * Time frame: experiments to be completed by **end 2021**
43: * Archiving: data will be archived at CPTEC
44: 
45: ==== 4. Activities proposed for 2020 ====
46: 
47: 
48: The major activities for planned for 2020 are:
49: 
50: 
51: 1. Organize teleconference between partners to coordinate experimental work (Feb 2020)
52: 1. Start running experiments with and without interactive dust and biomass burning.
53: 1. When ready, upload model outputs in the CPTC archive.
54: 
55: ==== 5. Resources ====
56: 
57: We mainly work through collaboration with WGNE, WMO/GAW and participating centres.
58: 
59: 
60: ==== 6. Linkages with WCRP/WWRP WGs & projects ====
61: 
62: We are directly linked to WGNE which has an activity on aerosols and which will conduct similar aerosol experiments for 48-hour forecasts. We also collaborate with WMO/GAW and also WMO/SDS who has a particular interest in dust prediction for meningitis prevention.
63: 
64: 
65: ==== References: ====
66: 
67: Benedetti, A., and F. Vitart, 2018: Can the direct effect of aerosols improve subseasonal predictability?Monthly Weather Review,146 (10), 3481–3498, doi:10.1175/MWR-D-17-0282.1, URLhttps:~/~/doi.org/10.1175/MWR-D-17-0282.1,https:~/~/doi.org/10.1175/MWR-D-17-0282.1.
68: 
69: Freitas, S. R., 2015: Evaluating aerosols impacts on numerical weather prediction:A wgne/wmo initiative.URL http:~/~/www.researchgate.net/publication/273258328 Evaluating aerosols impacts on Numerical Weather Prediction A WGNE WMO Initiative, last access: Apr 2019.
70: 
71: WWRP/WCRP, 2018: Wwrp/wcrp sub-seasonal to seasonal prediction project (s2s) phase ii proposal. URL https:~/~/www.wmo.int/pages/prog/arep/wwrp/new/documents/WWRP_2018_4_S2S_Phase_II_Proposal.pdf
72: 
73: Tian,B., D.Waliser, R.Kahn, Q.Li, Y.L.Yung,T.Tyranowski, I.Geogdzhayev, M.I.Mischenko and O.Torres, 2008 Does theMadden-Julian Oscillation Influence Aerosol Variability? Journal of Geophysical Research, 113(d12):D12215,doi:10.1029/2007JD009372 Tian, B.J.,D.E. Waliser, R.A. Kahn and S.Wong, 2011:Modulation of Atlantic aerosols by the Madden-Julian Oscillation, Journal of Geophysical Research: Atmospheres,116.
74: 
75: \\
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