Given the importance of the BL for a number of scientific research, applications, and modeling efforts, workshop participants explored specific aspects of BL research in detail. The following sections highlight interactions between the BL and the biosphere, land, ice, and ocean interfaces as well as the implications for modeling and parameterization. Panelists also examined specific applications such as air quality and human health impacts.
BL processes have impacts on the prediction of weather, S2S, and climate. In this panel, speakers discussed current limitations in numerical models as well as the types of observational efforts that would be most beneficial in addressing the limitations. Xubin Zeng noted that many observational data sources are used to evaluate climate model ABL clouds and height, radiation, precipitation, and humidity inversion. These include in situ observations, satellite information, and reanalysis. These types of observations can be used to evaluate beyond the basic atmospheric state, and it may be most beneficial to use long time series to assess climatological features. He also examined the importance of the land surface state relative to sea surface temperature (SST) for seasonal prediction over land and the impact of snow cover on seasonal prediction.
Parameter adjustments within models can lead to improvements, but it can be challenging to know which parameters to adjust and to understand the implications beyond those specific parts of the model. To highlight this, Ruby Leung discussed examples of Earth system model biases related to surface and BL processes, including dry bias in the western tropical Pacific and Amazon regions and low bias in oceanic stratocumulus clouds. She noted that parameters can be adjusted within parameterizations for gustiness and skewness of vertical velocity. Parameter changes can also have impacts beyond the intended area (e.g., improved polar cloud simulation with parameter changes intended to reduce stratocumulus bias). She raised some additional questions regarding the types of data that are needed to ensure that parameter changes are physically reasonable. She also challenged participants to consider the tradeoffs between routine observations with longer time series versus field campaigns with shorter but more detailed time series (i.e., greater spatial and temporal resolution).
Polar observations are limited compared to BL observations from lower latitudes. Scientists rely on data from field campaigns, but these are mostly of limited duration and do not observe everything that is needed to understand the observed BL features (e.g.,
Richardson number analysis1). The polar regions also have unique forcing (i.e., reduced importance of short wave radiation, surface cooling, heat and moisture advection from lower latitudes) and unique BL structures. Ola Persson addressed these unique forcings as well as some of the challenges associated with data collection in these regions. Surface cooling maintains low-level inversion in winter but warm-air advection aloft also generates inversion in the summer and winter. Cloud phase is important for surface forcing from warm air aloft. Melting surface conditions in summer reduce the role of short wave heating in driving convective mixing; mechanical mixing is more important.
A substantial portion of Earth’s biosphere resides within and has strong interactions with the atmospheric and other planetary BLs. Biological processes such as biodiversity and the distribution of species can be influenced by and can also influence atmospheric processes. Panelists explored changes in the atmosphere that can affect the biosphere as well as the impact that biosphere changes can have on atmospheric processes and composition. Ana Carnaval highlighted observations that advance the ability to detect and predict biodiversity, understand how it has changed in the past, and forecast how it might shift in the future. These observations are critical to biodiversity assessment and management. Biodiversity contributes to ecosystem functions and services that are important for human well-being, and there is an urgent need to globally assess and monitor changes in biodiversity. The distribution, diversity, and endemism of many groups of organisms can be well predicted by climate (specifically temperature and precipitation). Remote measurements of environmental variables at fine spatial resolution predict biodiversity better than interpolated weather station data (bioclimatic variables) in many parts of the world. Knowledge about past changes in biodiversity coupled with information about past environmental changes can provide promising new ways to predict future interactions between the biosphere and atmosphere, though uncertainties in modeling of biogeochemical processes need to be considered.
Currently, datasets that capture extreme events are hard to find, and they are incomplete spatially and temporally. Panelists noted that climate data acquired at daily or even diurnal time scales that can be used to determine extreme climate values globally could enhance biodiversity assessment. Scientists currently often rely on mean temperature and precipitation information, but remote sensing products with high temporal resolution might provide data that lead to advances in understanding. Possibilities for research advances include better ability to capture temporal complexity in environmental variables and to quantify biodiversity and biodiversity variables using remotely sensed data.
The terrestrial biosphere emits a broad suite of gases and particles into the ABL, and many of these compounds undergo transformations that produce ozone and fine
1 The dimensionless ratio of buoyant suppression of turbulence to shear generation of turbulence. It is used as a dynamic stability measure to determine if turbulence will exist. See http://glossary.ametsoc.org/wiki/Richardson_number.
particulate matter. Allison Steiner showed how trees and other plants contribute to BL atmospheric processes through emission of volatile organic compounds (VOCs) and pollen grains. Pollen plumes extend out during the day and can increase in elevation. Ruptured pollen grains can influence BL cloud formation by acting as cloud condensation nuclei. Also, the composition and diversity of plants influence atmospheric processes. For example, different species of trees produce different kinds of VOCs and only some lineages of trees emit isoprene (e.g., oaks, aspens, pines), which is produced as a byproduct of photosynthesis, and the amount emitted increases with temperature. Only some lineages of trees produce copious wind-dispersed pollen, and of those, different plant species have different phenology in terms of when they produce pollen. Methods of observing these phenomena include the use of lidar, which can be used to estimate pollen emissions and to detect when pollen plumes are emerging in the ABL, and aircraft, which can be used to detect isoprene emissions. BL mixing and chemical lifetimes (which vary with convection) can provide information on turbulence. Opportunities for research advances include finding parameterizations for models that work across a range of scales. From an observational perspective, greater availability of long-term datasets collected continuously at individual sites is needed, as noted by the panelists.
Organisms in the biosphere tend to be strongly influenced by light, temperature, water, and nutrient availability with consequences for land/ice/ocean-atmosphere exchanges. Kyle McDonald discussed the distribution and abundance of these organisms as well as some current methods to study and measure related variables. Surface moisture and water status define a surface hydrospheric state that is key to linking terrestrial water and energy cycles, and is a principal determinant of the terrestrial carbon cycle. Current and planned Earth science remote sensing missions offer a developing array of datasets supporting mapping and monitoring of land surface state variables associated with BL characterization. The NASA Soil Moisture Active Passive (SMAP) satellite can provide useful information on soil moisture globally (radiometrically) at relatively high resolution but not without caveats. It cannot detect soil moisture when there is dense vegetation above the soil, such as in forests, but it provides land surface freeze-thaw binary state measurement. The Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) seasonal methane flux study used aircrafts and flux towers to take measurements in the Alaskan Arctic. Methane emissions began with soil thaw and continued at lower levels after soil freezing occurred. The low level of emissions in fall make up a sizeable fraction of annual methane losses from the soil. Remotely sensed surface moisture levels can be used for climatic niche models that predict species distributions and diversity, as has been demonstrated in the Arctic and Amazon regions. One challenge is extending recent remote sensing observations back in time to capitalize on longer satellite datasets. Improvements are needed in radiometric data in terms of what they measure and how they should be interpreted. Lidar data are important for topography at high spatial resolution.
Additional measurement types and methods discussed by this panel included hyperspectral sensors at multiple spatial and temporal scales that can be important for monitoring plant biodiversity; hyperspectral data that allow retrieval of chemical and functional traits of plant canopies and spectral profiles of plants and plant canopies that
can be used to identify lineages; and detecting changes in functional diversity through time, a critical way to monitor biodiversity that contributes to ecosystem services.
Understanding the terrestrial BL involves dealing with complex terrain, stable and polar BLs, urban meteorology, and air quality. This panel attempted to identify challenges related to terrestrial BLs under stable conditions and over non-homogenous terrain and illustrate why it is important to improve current knowledge.
Terrain effects can be classified into synoptic effects and thermal circulations. In complex terrains, conventional BL scaling assumptions are violated. William Shaw highlighted that for wind energy, it is important to be able to deal with complex terrain and predications of winds at 100 m above ground level. This is also important for air quality, and quantification of errors could be better understood. In terms of observations, Dr. Shaw and Joe Fernando highlighted new remote sensing instrumentation that provides profiles as well as three-dimensional fields of wind, temperature, and turbulence. Dr. Shaw also highlighted the importance of long-term measurements, arguing that in situ observations for short-time periods are of limited value. Multi-scale studies that nest grids with different remote-sensing and in situ observations and operate over different seasons can provide the types of datasets (three-dimensional fields) needed for model evaluation studies. Progress has been made in the area of ground-based remote sensing, and Doppler wind lidars in particular provide useful data. Integrated approaches using observations and models, combining spatial and temporal information, are particularly important when dealing with complex terrain (see Figure 4).
LES is a powerful tool that can also be used to derive parameterizations, but questions remain concerning the subgrid-scale parameterizations, terrain-following coordinates versus Immersed Boundary Method, and robust nesting procedures that address possible grid discontinuities. Tina Katopodes Chow suggested that model intercomparisons and evaluation studies are critical and it may be time for a new paradigm for how these are conducted. A better coordinated approach is needed with multiple modeling groups all working together to tackle specific problems. If this type of coordination can be achieved, a more comprehensive model could be developed that better captures the complexities of the problem (a hyper-model with ultra capabilities in areas such as physical parameterizations, computing efficiency, and others). This could be linked to field campaigns to provide better access to model data during the campaigns, to facilitate strategies for how to use new emerging datasets together, and possibly also to better define goals and timelines for when milestones must be completed.
The MBL plays a key role in BL studies through momentum transfer from atmosphere to ocean, turbulent and radiative air-sea fluxes, and interactions with biogeochemistry (i.e., coupled atmosphere-ocean biogeochemistry). In this panel, William Drennan discussed the wave model source term (energy input from winds to waves) as presented in current generation wave models. There have been few advances since the early 1990s to improve knowledge, and growth parameterizations rely on limited data from the 1970s and 1980s. Direct pressure measurements over waves are crucial, but they are hard to make and the dissipation term is still diagnosed as residual in the energy balance equation. He also discussed air-sea fluxes at high wind speeds, which are important in cyclones and hurricanes. Data are available for drag coefficients, but from different sensors, platforms, and conditions, and these are not readily comparable. In terms of opportunities, new autonomous platform technologies will likely be significant. In addition, high-resolution directional wave measurements at high winds would be valuable. Finally, Dr. Drennan discussed high-
latitude air-sea fluxes and noted that high latitude efforts could include improved measurements, measurement capabilities, remote sensing, and modeling.
Climate sensitivity to MBL clouds is a leading source of uncertainty. Simon de Szoeke pointed out the importance of the interactions across scales, which require observations of key processes in isolation. High-resolution MBL observations have been enhanced by process studies, for example, the diurnal cycle of stratocumulus cloud top turbulence, cloud microphysical interactions, and BL-cumulus interaction. New opportunities for in situ measurements include autonomous platforms, miniature, low-cost, and low-power sensors as well as turbulent fluxes of additional scalars, e.g., water isotopologues. New opportunities in remote sensing include space- and ground-based instruments, ranging, and scanning as well as Doppler (spectra), multiple wavelengths, and polarization sensing.
The cloudy MBL plays an important role in property transport, cloud feedback, and aerosol forcing. Robert Wood discussed observational needs, key physical processes, and required space and time scales. There are critical measurement gaps (e.g., vertical structure), and existing observations could be better leveraged to address these gaps. It will be important to combine, package, and distribute disparate datasets to make them more readily usable. New measurements to be developed in the next decade include improvements in miniaturization (e.g., small drones). On a multi-decadal time scale, opportunities for new measurements include wide/multiple-field view lidar and multi-wavelength radar. Intensive field campaigns used synergistically with satellite and surface sampling can help improve sampling needs. Autonomous platforms, miniaturization, and drones could also provide opportunities to collaborate with various industries and startups that are working on developing these technologies.
There is a need to go beyond traditional BL parameterization to properly model, for example, embedded organized structures due to roll vortices and the impacts of roll vortices on sea surface fluxes, surface driven organized structures due to ocean waves, and processes within flows driven by complex topography and stratification. In this panel, speakers noted that waves are critically important; they are the roughness elements that support momentum, heat, and mass exchange between the atmosphere and the ocean. Peter Sullivan, Ralph Foster, and David Randall discussed these types of BL modeling and parameterizations and how to move beyond traditional closure schemes, for example, to go beyond down-gradient diffusion models to more accurately model non-local processes; to go beyond traditional subfilter scale parameterization in LES (e.g., Dynamic Reconstruction Model [DRM] as opposed to eddy-viscosity closure); and to develop scale dependent parameterizations. Panelists noted that improved modeling of clouds and cloud forcing will remain important for BL research and coupled models. Similar effort could be taken to improve parameterization of surface fluxes, flux-profile relationships, and non-local effects throughout the BL. Multiple workshop participants noted the importance of the vertical structure of the fluxes within the BL. Designing field experiments that include models,
simulations, and observations can help to develop, improve, validate, and use these models.
Chemical composition of the BL is critical for a number of societal issues. People live in the BL, and it is of particular importance for a variety of applications, including understanding evolution of hazardous pollutant concentrations and health impacts as well as air quality predictions. BL characteristics are critical for understanding, interpreting, and predicting chemical composition and pollutant emissions (for example, wildfires and dust) in this atmospheric region. James Whetstone, Ronald Cohen, Ivanka Stajner, and Sherri Hunt raised a number of key points regarding the chemical composition of the BL. They noted that measurements of chemical species (with high frequency and spatial resolution) could be helpful in characterizing the BL and understanding its dynamics.
In particular, panelists noted that there is a desire to characterize the stable BL (often associated with air quality exceedances) and potential intermittent turbulence. Representation of the BL in current models is not adequate for current research needs. Higher resolution modeling appears to improve the BL representations, but the relevant processes may not be parameterized correctly. Assimilation of chemical data may help improve BL characterization (NO2 is a good candidate; see Figure 5). Lower-cost, high sensitivity sensors can help with dense measurement systems for air quality and GHG issues. Urban emissions are being quantified and connecting top-down and bottom-up emissions is ongoing, but there may still be room for improvement.