Chemical and Biological Meteorology

Scientists across NCAR are conducting research in this interdisciplinary topic through efforts such as: the Deep Convective Clouds and Chemistry (DC3) field campaign, which links the cloud physics and dynamics, electricity, and atmospheric chemistry communities. DC3 field campaign analysis studies included characterizing the outflow of the 22 June 2012 case that had a biomass-burning plume ingested into the storm (see figure 1), determining the scavenging efficiencies of soluble trace gases via data analysis and modeling, characterizing the wrapping of stratospheric air around anvils associated with mesoscale convective systems (see figure 2), and contributing to colleagues’ papers. Analysis of DC3 data enhances understanding of how convection affects tropospheric composition, especially ozone, which acts as a radiatively active greenhouse gas in the upper troposphere. These efforts are expected to improve model parameterizations of convective transport, production of nitrogen oxides from lightning, and wet deposition of chemical species.

NEXRAD Radar Composite
Figure 1: (Top panel) NEXRAD radar composite reflectivity of the Colorado-Nebraska convection studied during the 22 June 2012 research flights. The image is overlaid with DC-8 and GV flight tracks. The far left red circle indicates the High Park fire origin. The purple oval indicates the approximate location of the north storm outflow, and the gold oval the south storm outflow. Panels a-f): GV measurements along the flight track color coded according to the species mixing ratio and sized with altitude (small filled circles are at low altitude). (a) Ozone, (b) NO, (c) CO, (d) formaldehyde, (e) acetonitrile, and (f) n-butane.
These results show high ozone just to the north of the storm anvil, low ozone within the anvil. NO and n-butane are higher in the south storm outflow than the north storm outflow, while CO, formaldehyde, and acetonitrile are higher in the north storm outflow. Acetonitrile is a marker of biomass burning, indicating that the north storm ingested biomass burning from the High Park fire. Model calculations of the chemistry in the two storm outflows report more ozone production occurring in the south storm outflow over the next 48 hours than in the north storm outflow, because of the higher NO in the south storm outflow. Apel, E. C. et al. (2015), Upper tropospheric ozone production from lightning NOx-impacted convection: Smoke ingestion case study from the DC3 campaign. J. Geophys. Res. Atmos., 120, 2505–2523. doi: 10.1002/2014JD022121.


Ozone Measurements
Figure 2: The vertical distribution of upper tropospheric ozone mixing ratio (upper) measured by DIAL along approximately 30 minutes (~ 400 km in distance) of the DC-8 flight. Note the cross section is shown in reversed time scale to illustrate the cross section from west to east. The black color indicates the region when the DIAL ozone channel produced no data due to cloud attenuation.  In situ ozone is shown by the color of the flight track.  The depolarization ratio (lower panel) from the DIAL 355 nm wavelength channel provides a signature of cloud/storm edge and outflow pattern in the neighborhood of the storm.  The outflow structure shown in light blue is most consistent with low number density of ice particles, which complements the stretching and shedding shown in the ozone structure (upper panel).
Pan, L. L. et al. (2014), Thunderstorms Enhance Tropospheric Ozone by Wrapping and Shedding Stratospheric Air, Geophys. Res. Lett. , 41, 7785–7790, doi:10.1002/2014GL061921.

The biome has considerable effects on weather and atmospheric composition on a variety of time scales.  Diurnally varying interactions of canopies with the near-surface layer of the atmosphere fundamentally alter the transport of constituents into the atmosphere.  In the extreme case of wildfire, modeling requires turbulence resolving models interacting with complex physics of fire. The basic process of these surface/canopy/atmosphere interactions requires detailed investigations to quantify how their aggregate effects can be incorporated into earth system prediction efforts.

Analysis of canopy turbulence observations and simulations improves understanding and modeling of turbulent momentum, energy, and trace gas exchange between vegetation and the atmosphere.  In FY 2015 the role of tree phenology on atmospheric turbulence parameterization over tall deciduous vegetation was investigated and quantified using observations from the Canopy Horizontal Array Turbulence Study (CHATS) field experiment to establish the dependence of the turbulent exchange of momentum, heat, and moisture, as well as kinetic energy on canopy phenological evolution through widely used parameterizations based on: a) dimensionless gradients, or b) turbulent kinetic energy (TKE) in the roughness sublayer. Observed vertical turbulent fluxes and gradients of mean wind, temperature, and humidity are used in combination with empirical dimensionless functions to calculate the exchange coefficient. The analysis shows that changes in canopy phenology influence the turbulent exchange of all quantities analyzed (see figure 3). The turbulent exchange coefficients are twice as large near the canopy top for the leafless canopy than for the fully leafed canopy under unstable and near-neutral conditions. This difference in the turbulent exchange coefficient is related to different penetration depth of the turbulent eddies organized at the canopy top, which increases for a canopy without leaves. Analysis of the TKE and its dissipation under near-neutral atmospheric conditions shows that TKE exchange increases for a leafless canopy due to reduced TKE dissipation efficiency compared to that when the canopy is in full-leaf. The study closed with discussion surrounding the implications of these findings for parameterizations used in large-scale models.


Figure 3: Evolution of the dimensionless gradients for momentum, heat and moisture at 2.3 (a, b, c, respectively), 1.4 (d, e, f, respectively) and 1.1 (g, h, I, respectively) times the canopy height above a walnut orchard during the CHATS field campaign; the open red and full green triangles represent the observations during periods when the canopy was leafless and with-leaves, respectively; the black dashed lines represent the traditional Monin-Obukhov Similarity Theory (MOST) formulation relating a wind speed gradient to the momentum flux, while the solid blue solid lines show dimensionless gradients for momentum and scalars modified to account for canopy-induced modification to MOST.  (Shapkalijevski et al., J. Appl. Meteorol. Clim. accepted.)

In another related effort, MMM and ACOM scientists analyzed ground based and aircraft observations of the photochemistry of isoprene (C5H8) and related chemical species in the sunlit daytime convective boundary layer (CBL) from the Southern Oxidant and Aerosol Study (SOAS), which focused on the coupling between biogenic and anthropogenic reactant sources on secondary organic aerosol production above a mixed forest. Fluxes of isoprene and monoterpenes were quantified at the top of the forest canopy using a high-resolution Proton Transfer Reaction Time of Flight Mass Spectrometer (PTR-TOF-MS). Both ground-based and airborne collected volatile organic compounds (VOC) data are used to constrain the initial conditions of a mixed layer chemistry model (MXLCH), which is applied to examine the chemical evolution of the O3-NOx-HOx-VOC system and how it is affected by boundary layer dynamics in the CBL. The chemical loss rate of isoprene (~1h) is similar to the turbulent mixing time scale (0.1-0.5 h), which indicates that isoprene concentrations are equally dependent on both photo-oxidation and boundary layer dynamics (see figure 4). Budget analyses suggest that diurnal evolution of isoprene inside the CBL is mainly controlled by surface emissions and chemical loss.

Model Graph

Figure 4: :  Model output showing the influence of dynamics and chemistry on the time evolution of isoprene and ozone in the boundary layer during an ideal clear-day during the SOAS experiment that took place near Centreville, AL in June-July 2013.  These results emphasize the clear influence of boundary layer entrainment on the diurnal cycle of key atmospheric constituents.  (Su et al., Atmos. Chem. Phys., submitted.)

Other work in FY 2015 included implementation of a multi-level roughness sublayer parameterization in an offline version of the Community Land Model (CLM).  Preliminary testing of the parameterization using AmeriFlux observations to drive CLM reveals distinct improvement in predicted momentum, sensible, and latent heat fluxes (see figure 5). Further testing over crops and tropical forest regions are ongoing.

Community Land Model Graphs

Figure 5:  An average diurnal cycle of surface exchange predicted by an offline version of the Community Land Model modified to predict stomatal conductance by linking leaf water-use efficiency and water transport along the soil–plant–atmosphere (SPA) continuum. The green line represents results produced by driving the SPA version of CLM with observed variables above the canopy at Harvard Forest during July of 1993.  The red line represents surface exchange predicted by the SPA version of CLM driven