WRF Simulations of Passive Tracer Transport from Biomass Burning in South America: Sensitivity to PBL Schemes

article
Autores

De Bem, Douglas Lima

Anabor, Vagner

Pinheiro, Damaris Kirsch

Steffenel, Luiz Angelo

Bencherif, Hassan

Bittencourt, Gabriela Dornelles

Landulfo, Eduardo

Rizza, Umberto

Data de Publicação

19 de outubro de 2025

Resumo

This single high-impact case study investigates the impact of planetary boundary layer (PBL) representation on long-range transport of Amazon fire smoke that reached the Metropolitan Area of São Paulo (MASP) from 15 to 20 August 2019, using the WRF model to compare three PBL schemes (MYNN 2.5, YSU, and BouLac) and three source-tagged tracers. The simulations are evaluated against MODIS-derived aerosol optical depth (AOD), the Light Detection and Ranging (LiDAR) time–height curtain over MASP, and HYSPLIT forward trajectories. Transport is diagnosed along the source-to-MASP pathway using six-hourly cross-sections and two integrative metrics: the projected mean wind in the 700–600 hPa layer and the vertical moment of tracer mass above the boundary layer. Outflow and downwind impact are strongest when a persistent reservoir between 2 and 4 km coexists with projected winds for several hours. In this episode, MYNN maintains an elevated 2–5 km transport layer and matches the observed arrival time and altitude, YSU yields a denser but delayed column, and BouLac produces discontinuous pulses with reduced coherence over the city. A negatively tilted trough, jet coupling, and a nearly stationary front establish a northwest-to-southeast corridor consistent across model fields, trajectories, and satellite signal. Seasonal robustness should be assessed with multi-event, multi-model analyses.

Citação

BibTeX
@online{bem,_douglas_lima2025,
  author = {Bem, Douglas Lima, De and Vagner , Anabor and Damaris Kirsch
    , Pinheiro and Luiz Angelo , Steffenel and Hassan , Bencherif and
    Gabriela Dornelles , Bittencourt and Eduardo , Landulfo and Umberto
    , Rizza},
  title = {WRF Simulations of Passive Tracer Transport from Biomass
    Burning in South America: Sensitivity to PBL Schemes},
  volume = {17},
  number = {20},
  date = {2025-10-19},
  doi = {10.3390/rs17203483},
  langid = {pt-BR},
  abstract = {This single high-impact case study investigates the impact
    of planetary boundary layer (PBL) representation on long-range
    transport of Amazon fire smoke that reached the Metropolitan Area of
    São Paulo (MASP) from 15 to 20 August 2019, using the WRF model to
    compare three PBL schemes (MYNN 2.5, YSU, and BouLac) and three
    source-tagged tracers. The simulations are evaluated against
    MODIS-derived aerosol optical depth (AOD), the Light Detection and
    Ranging (LiDAR) time–height curtain over MASP, and HYSPLIT forward
    trajectories. Transport is diagnosed along the source-to-MASP
    pathway using six-hourly cross-sections and two integrative metrics:
    the projected mean wind in the 700–600 hPa layer and the vertical
    moment of tracer mass above the boundary layer. Outflow and downwind
    impact are strongest when a persistent reservoir between 2 and 4 km
    coexists with projected winds for several hours. In this episode,
    MYNN maintains an elevated 2–5 km transport layer and matches the
    observed arrival time and altitude, YSU yields a denser but delayed
    column, and BouLac produces discontinuous pulses with reduced
    coherence over the city. A negatively tilted trough, jet coupling,
    and a nearly stationary front establish a northwest-to-southeast
    corridor consistent across model fields, trajectories, and satellite
    signal. Seasonal robustness should be assessed with multi-event,
    multi-model analyses.}
}
Por favor, cite este trabalho como:
Bem, Douglas Lima, De, Anabor Vagner, Pinheiro Damaris Kirsch, Steffenel Luiz Angelo, Bencherif Hassan, Bittencourt Gabriela Dornelles, Landulfo Eduardo, and Rizza Umberto. 2025. “WRF Simulations of Passive Tracer Transport from Biomass Burning in South America: Sensitivity to PBL Schemes.” Remote Sensing. October 19, 2025. https://doi.org/10.3390/rs17203483.