Mena-Carrasco M, Saide P, Delgado R, Hernandez P, Spak S, Molina L, Carmichael G, Jiang X. Regional climate feedbacks in Central Chile and their effect on air quality episodes and meteorology. Urban Climate [Internet]. 2014;10 (Part 5) :771 - 781. Publisher's Version
Saide PE, Carmichael GR, Liu Z, Schwartz CS, Lin HC, da Silva AM, Hyer E. Aerosol optical depth assimilation for a size-resolved sectional model: impacts of observationally constrained, multi-wavelength and fine mode retrievals on regional scale analyses and forecasts. Atmospheric Chemistry and Physics [Internet]. 2013;13 (20) :10425–10444. Publisher's Version
Twohy CH, Anderson JR, Toohey DW, Andrejczuk M, Adams A, Lytle M, George RC, Wood R, Saide P, Spak S, et al. Impacts of aerosol particles on the microphysical and radiative properties of stratocumulus clouds over the southeast Pacific Ocean. Atmospheric Chemistry and Physics [Internet]. 2013;13 (5) :2541–2562. Publisher's Version
Saide PE, Carmichael GR, Spak SN, Minnis P, Ayers JK. Improving aerosol distributions below clouds by assimilating satellite-retrieved cloud droplet number. Proceedings of the National Academy of Sciences [Internet]. 2012;109 (30) :11939-11943. Publisher's VersionAbstract
Limitations in current capabilities to constrain aerosols adversely impact atmospheric simulations. Typically, aerosol burdens within models are constrained employing satellite aerosol optical properties, which are not available under cloudy conditions. Here we set the first steps to overcome the long-standing limitation that aerosols cannot be constrained using satellite remote sensing under cloudy conditions. We introduce a unique data assimilation method that uses cloud droplet number (Nd) retrievals to improve predicted below-cloud aerosol mass and number concentrations. The assimilation, which uses an adjoint aerosol activation parameterization, improves agreement with independent Nd observations and with in situ aerosol measurements below shallow cumulus clouds. The impacts of a single assimilation on aerosol and cloud forecasts extend beyond 24 h. Unlike previous methods, this technique can directly improve predictions of near-surface fine mode aerosols responsible for human health impacts and low-cloud radiative forcing. Better constrained aerosol distributions will help improve health effects studies, atmospheric emissions estimates, and air-quality, weather, and climate predictions.
Saide PE, Spak SN, Carmichael GR, Mena-Carrasco MA, Yang Q, Howell S, Leon DC, Snider JR, Bandy AR, Collett JL, et al. Evaluating WRF-Chem aerosol indirect effects in Southeast Pacific marine stratocumulus during VOCALS-REx. Atmospheric Chemistry and Physics [Internet]. 2012;12 (6) :3045–3064. Publisher's Version
Mena-Carrasco M, Oliva E, Saide P, Spak SN, de la Maza C, Osses M, Tolvett S, Campbell JE, es Tsao TC-C, Molina LT. Estimating the health benefits from natural gas use in transport and heating in Santiago, Chile. Science of The Total Environment [Internet]. 2012;429 (Supplement C) :257 - 265. Publisher's Version
Saide P, BOCQUET MARC, OSSES AXEL, GALLARDO LAURA. Constraining surface emissions of air pollutants using inverse modelling: method intercomparison and a new two-step two-scale regularization approach. Tellus B [Internet]. 2011;63 (3) :360–370. Publisher's Version
Shrivastava M, Fast J, Easter R, Gustafson Jr. WI, Zaveri RA, Jimenez JL, Saide P, Hodzic A. Modeling organic aerosols in a megacity: comparison of simple and complex representations of the volatility basis set approach. Atmospheric Chemistry and Physics [Internet]. 2011;11 (13) :6639–6662. Publisher's Version
Saide PE, Carmichael GR, Spak SN, GALLARDO LAURA, Osses AE, Mena-Carrasco MA, Pagowski M. Forecasting urban PM10 and PM2.5 pollution episodes in very stable nocturnal conditions and complex terrain using WRF–Chem CO tracer model. Atmospheric Environment [Internet]. 2011;45 (16) :2769 - 2780. Publisher's Version
Saide P, Zah R, Osses M, de Eicker MO. Spatial disaggregation of traffic emission inventories in large cities using simplified top–down methods. Atmospheric Environment [Internet]. 2009;43 (32) :4914 - 4923. Publisher's Version