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Learning lessons from Amazonia to Ruisdael

This study examines the interconnected biophysical processes and weather interactions in the Amazon rainforest to understand the impacts on energy, water, and carbon cycles. The research findings provide insights into the effects of shallow convection, moisture recycling, and biomass burning on the Amazon basin's precipitation and overall ecosystem.

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Learning lessons from Amazonia to Ruisdael

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  1. Learning lessons from Amazonia to Ruisdael Jordi Vilà Meteorology and Air Quality Section Wageningen University

  2. ...we estimate reductions 21 per cent in the dry seasonprecipitation respectively across the Amazon basin by 2050, due to less-efficient moisture recycling (Spracklen et al., 2012) ...rainforest transpiration enables an increase of shallow convection that moistens and destabilizes the atmosphere during the initial stages of the dry-to-wet season transition (Wright et al. 2017) ...The total drought response in the Amazon in our estimates is distributed between additional biomass burning and reduced net biomass (CO2) exchange uptake (van der Laan-Luijkx et al., 2015)

  3. The Green-White Amazonian Rainforest 10-09-2014 14-09-2014 Understanding the energy, water and carbon cycles at the sub-daily and sub-kilometre scales

  4. Biophysical processes interconnected to weather

  5. Research strategy: integrating methods

  6. Understanding: Large-eddy simulation 50 m x 50 m x 20 m PhD thesis Sikma (2019)

  7. Representing: ECMWF-Integrated Forecasting System 9 km x 9 km x 20 m Bousseta et al. (2013)

  8. Observations: GoAmazoncampaign September 2014 • Comprehensive 4D data set • K34 tower (60 km NW Manaus) • 40 meter above the canopy • Radiosoundings state variables • ARM-Mobile facility: • Cloud properties (Martin et al., 2017)

  9. Dry-to-wet season: September 2014 10-09-2014 • For numerical experiment one • representative day • - DALES • - ECMWF • For observations, a monthly • mean aggregate to study the • variability, minimum and maximum • values 100 km

  10. Midday plant depression: fluxes CO2 above the canopy

  11. Midday plant depression: fluxes CO2 above the canopy • CO2 assimilation and • plant transpiration differs from • morning to afternoon • Hysteresis loop depends on • soil moisture to water vapour • pressure deficit (demand atmosphere) • Similar timing onset shallow • cumulus convection • When does dial terrestrial update • becomes a source or a skink?

  12. CO2 diurnal variability: Mixing ration above the canopy • CO2 diurnal variability depending on: • - Local sources/sinks in the • canopy • - Entrainment residual layer and • free troposphere • - Large-scale transport

  13. Interaction canopy-atmosphere: CO2 vertical variability • CO2 profiles in and in the roughness • sublayer remains a challenge • Disagreement between DALES and • ECMWF in the sub-cloud layer • Interaction between large-scale CO2 • spatial distributionand local sources • and sinks

  14. Transition dry-to-wet convection

  15. Moistening and destabilization above cloud base • Thermodynamic profiles follow • typical vertical structure shallow • convection • Small monthly observational • variability during the month • September • Reduce moistening and • destabilization above cloud base • by ECMWF • Impact in triggering deep • convection

  16. Cloud cover and liquid water path: Disentangling fog, shallow and deep convection • DALES reproduces well the • transition from clear to • shallow cumulus • Open challenges with respect to • the morning fog and the transition • from shallow to deep convection • Observing liquid water content • by radar (small droplets, drizzle) • with larger uncertainties

  17. Cloud cover variation with height DALES • Possibility to compare the variation • of cloud cover with height: • DALES versus radar observations • (W band + LIDAR) • Similar vertical distribution • in the diurnal variation: from 10 to 15 LT • Underestimation DALES compared to • the observations... • But are we comparing the same? OBSERVATIONS

  18. Learning lessons with respect to the Ruisdael TestBed • Coupling biochemical and physical processes • - Advanced level on implementation of processes and verification • - Not yet there in relation to microphysics, radiation and • canopy-atmosphere interactions • Interaction spatiotemporal scales • Ruisdael TestBed: • Integrating large-scale weather/CO2 and small spatiotemporal scales • Moving forward on atmospheric sciences • - Identifying gaps of knowledge on scientific topics: • midday depression and transition shallow to deep convection

  19. Ventilation CO2 by shallow convection

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