Interactions Between the Amazonian Rainforest and Cumuli Clouds: A Large‐Eddy Simulation, High‐Resolution ECMWF, and Observational Intercomparison Study

The explicit coupling at meter and second scales of vegetation's responses to the atmospheric‐boundary layer dynamics drives a dynamic heterogeneity that influences canopy‐top fluxes and cloud formation. Focusing on a representative day during the Amazonian dry season, we investigate the diurnal cycle of energy, moisture and carbon dioxide at the canopy top, and the transition from clear to cloudy conditions. To this end, we compare results from a large‐eddy simulation technique, a high‐resolution global weather model, and a complete observational data set collected during the GoAmazon14/15 campaign. The overall model‐observation comparisons of radiation and canopy‐top fluxes, turbulence, and cloud dynamics are very satisfactory, with all the modeled variables lying within the standard deviation of the monthly aggregated observations. Our analysis indicates that the timing of the change in the daylight carbon exchange, from a sink to a source, remains uncertain and is probably related to the stomata closure caused by the increase in vapor pressure deficit during the afternoon. We demonstrate quantitatively that heat and moisture transport from the subcloud layer into the cloud layer are misrepresented by the global model, yielding low values of specific humidity and thermal instability above the cloud base. Finally, the numerical simulations and observational data are adequate settings for benchmarking more comprehensive studies of plant responses, microphysics, and radiation

Quantifying feedbacks in the plant-atmosphere-cloud continuum

The main objective of this thesis was to gain insights on the impact of diurnal and local interactions between the vegetation, atmosphere and boundary layer clouds in current and future atmospheres. Special focus was placed on the consequences on moist convection, as it is one of the main uncertainties in the global climate and weather models. Moist convection is strongly influenced by the vegetated surface characteristics, which has consequences on the sub-weekly atmospheric state. In this thesis, a balanced approach is taken, which takes into account local (meters) and short (minutes) dynamic vegetation responses to atmospheric and cloud perturbations, that subsequently influence the atmospheric boundary layer and cloud development. To deepen our understanding of the processes that act on the smaller scales, a Large-Eddy Simulation (LES) model was employed and coupled with a mechanistic land-surface submodel. The LES model explicitly resolved the various dynamical processes at a scale of 50 m, which has an advantage over the coarser atmospheric models as minimal parametrizations are required. The investigations were based on a combined approach of advanced measurements and numerical experiments. The numerical experiments are based on observations over Western Europe, while for the future atmospheres the numerical experiments were inspired on results from a Free-Air CO2 Enrichment (FACE) experiment in Japan and combined with findings from literature. By following a systematic approach, our results highlighted the regional effects of a strong plant-atmosphere-cloud coupling (Chapter 2). In low wind and convective situations, a lowering in surface energy fluxes resulted in stabilized cloud development, although there was a distinct response based on the cloud optical properties. With increasing background wind, atmospheric roll vortices forced the cloud population into streets (i.e., parallel strips of clouds alternated by clear sky). As a consequence of an asymmetric stomatal plant response, vegetation streaks arose due to cloud shading that negatively affected the surface energy balance. This result shed light to a new coupling mechanism that constrained cloud development and reduced the in-cloud moisture flux (Chapter 3). To determine whether the plant-atmosphere-cloud coupling could be captured by homogeneous surface responses (i.e., related to a response in a NWP or GCM grid box), we performed simulations that were similar in the domain averaged surface energy, but differed in their response: interactive versus prescribed (Chapter 3). Our findings showed that large misrepresentation of up to 56% occurred in the regional moisture flux when the locality of the dynamic plant responses to atmospheric perturbations was not taken into account. This highlighted the need that these atmospheric flow dependent plant-atmosphere-cloud interactions need to be included in the parameterizations of the coarser NWPs and GCMs. By analyzing a comprehensive observational FACE dataset of two distinct rice varieties in ambient and elevated CO2 environments (+200 ppm) in Chapter 4, we identified a strong interplay between influencers on the plant-atmosphere interaction. In elevated CO2 environments, the physiological response to this factor became apparent, with warmer and drier in-canopy levels in a more closed and less photosynthetic active canopy, while the opposite was found in a more open and photosynthetic active canopy. Inspired by our findings of Chapter 4, we simulated and investigated the sensitivity of plant responses to elevations in both air temperature (+2 K) as [CO2] (+200 ppm) in Chapter 5. Our findings showed contrasting responses to elevations in temperature and [CO2] on the surface energy balance and momentum transfer. Elevations in temperature yields enhanced plant transpiration, thus latent heat flux, and reduced the sensible heat flux. As a consequence, the turbulent kinetic energy and buoyancy rates reduced, which caused reductions in cloud cover and mid-tropospheric moisture transport. With elevations in [CO2], a distinct response occurred, leading to higher sensible heat fluxes and lower plant transpiration and latent heat fluxes. With more momentum in the atmospheric boundary layer, clouds were able to become deeper and transport more moisture into the troposphere. When simulating a future atmosphere with both elevations in temperature and [CO2] in Chapter 5, we found an offset in the surface energy balance with nearly identical energy fluxes as compared to current situations. However, the plant physiological state was affected, with reductions in plant transpiration and increased CO2 assimilation. In conclusion, our results highlight the necessity of small scales and interactions, which require a bottom-up approach to be able to accurately capture the nonlinear plant-atmosphere interactions. Neglecting these interactions cause the coarser global climate and numerical weather prediction models to be liable to misrepresentations when modelling current and future atmospheres.</p

Supplementary data of "Japan FACE 2015 experiment"

This dataset contains data from the 2015 Japan FACE experiment and covers 2 rice varieties in ambient and elevated CO2 conditions. The data contains microclimate measurements of in-canopy and above-canopy atmospheric variables

Substantial Reductions in Cloud Cover and Moisture Transport by Dynamic Plant Responses

Cumulus clouds make a significant contribution to the Earth's energy balance and hydrological cycle and are a major source of uncertainty in climate projections. Reducing uncertainty by expanding our understanding of the processes that drive cumulus convection is vital to the accurate identification of future global and regional climate impacts. Here we adopt an interdisciplinary approach that integrates interrelated scales from plant physiology to atmospheric turbulence. Our explicit simulations mimic the land-atmosphere approach implemented in current numerical weather prediction, and global climate models enable us to conclude that neglecting local plant dynamic responses leads to misrepresentations in the cloud cover and midtropospheric moisture convection of up to 21% and 56%, respectively. Our approach offers insights into the key role played by the active vegetation on atmospheric convective mixing that has recently been identified as the source of half of the variance in global warming projections (i.e., equilibrium climate sensitivity).</p

Increasing canopy photosynthesis in rice can be achieved without a large increase in water use-A model based on free-air CO2 enrichment

Achieving higher canopy photosynthesis rates is one of the keys to increasing future crop production; however, this typically requires additional water inputs because of increased water loss through the stomata. Lowland rice canopies presently consume a large amount of water, and any further increase in water usage may significantly impact local water resources. This situation is further complicated by changing the environmental conditions such as rising atmospheric CO2 concentration ([CO2]). Here, we modeled and compared evapotranspiration of fully developed rice canopies of a high-yielding rice cultivar (Oryza sativa L. cv. Takanari) with a common cultivar (cv. Koshihikari) under ambient and elevated [CO2] (A-CO2 and E-CO2, respectively) via leaf ecophysiological parameters derived from a free-air CO2 enrichment (FACE) experiment. Takanari had 4%-5% higher evapotranspiration than Koshihikari under both A-CO2 and E-CO2, and E-CO2 decreased evapotranspiration of both varieties by 4%-6%. Therefore, if Takanari was cultivated under future [CO2] conditions, the cost for water could be maintained at the same level as for cultivating Koshihikari at current [CO2] with an increase in canopy photosynthesis by 36%. Sensitivity analyses determined that stomatal conductance was a significant physiological factor responsible for the greater canopy photosynthesis in Takanari over Koshihikari. Takanari had 30%-40% higher stomatal conductance than Koshihikari; however, the presence of high aerodynamic resistance in the natural field and lower canopy temperature of Takanari than Koshihikari resulted in the small difference in evapotranspiration. Despite the small difference in evapotranspiration between varieties, the model simulations showed that Takanari clearly decreased canopy and air temperatures within the planetary boundary layer compared to Koshihikari. Our results indicate that lowland rice varieties characterized by high-stomatal conductance can play a key role in enhancing productivity and moderating heat-induced damage to grain quality in the coming decades, without significantly increasing crop water use

DALES - Dutch Atmospheric Large Eddy Simulation

The version of DALES used on Fugaku for the Cloud Botany dataset

dalesteam/dales: v4.3 for Cloud Botany on Fugaku

The version of DALES used on Fugaku for the Cloud Botany dataset. Adds support for the Fujitsu compiler for running on Fugaku, and several optimizations to version 4.3: single precision support better vectorization faster thermodynamics Most of these changes have subsequently been merged into the official v4.4 release.</p

franslql/dales: DALES 4.4 with open boundary conditions

&lt;p&gt;DALES 4.4 code with open boundary conditions and scripts for publication &quot;Open Boundary Conditions for Atmospheric Large Eddy Simulations and their implementation in DALES4.4&quot;.&lt;/p&gt

Advancing understanding of land–atmosphere interactions by breaking discipline and scale barriers

Vegetation and atmosphere processes are coupled through a myriad of interactions linking plant transpiration, carbon dioxide assimilation, turbulent transport of moisture, heat and atmospheric constituents, aerosol formation, moist convection, and precipitation. Advances in our understanding are hampered by discipline barriers and challenges in understanding the role of small spatiotemporal scales. In this perspective, we propose to study the atmosphere–ecosystem interaction as a continuum by integrating leaf to regional scales (multiscale) and integrating biochemical and physical processes (multiprocesses). The challenges ahead are (1) How do clouds and canopies affect the transferring and in-canopy penetration of radiation, thereby impacting photosynthesis and biogenic chemical transformations? (2) How is the radiative energy spatially distributed and converted into turbulent fluxes of heat, moisture, carbon, and reactive compounds? (3) How do local (leaf-canopy-clouds, 1 m to kilometers) biochemical and physical processes interact with regional meteorology and atmospheric composition (kilometers to 100 km)? (4) How can we integrate the feedbacks between cloud radiative effects and plant physiology to reduce uncertainties in our climate projections driven by regional warming and enhanced carbon dioxide levels? Our methodology integrates fine-scale explicit simulations with new observational techniques to determine the role of unresolved small-scale spatiotemporal processes in weather and climate models