Vegetation demographics in Earth System Models: A review of progress and priorities

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). These developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. Here, we review the developments that permit the representation of plant demographics in ESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections but also allow models to be applied to new processes and questions concerning the dynamics of real-world ecosystems. We argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first-generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter-disciplinary communication

Horizontal and vertical forest complexity interact to influence potential fire behavior

2022 Spring.Includes bibliographical references.Wildland fire behavior is a dynamic process controlled by complex interactions among fuels, weather, and topography. There is significant need to better understand the role of fuels and, particularly, complex arrangements of fuels, on potential fire behavior and effects as a there is a growing emphasis on forest treatments that emulate the heterogenous structures of historical forest ecosystems. Ideally such treatments are intended to reduce fire hazard while concurrently improving resilience to a wide range of disturbance agents and restoring the natural ecosystem dynamics that maintained these forest structures. One way to evaluate how the complex forest structures created by these treatments will influence fire behavior are modeling approaches that account for dynamic interactions between fire, fuels, and wind. These physical fire models build from computational fluid dynamics methods to include processes of heat transfer, vegetative fuel dehydration and pyrolysis, and gas phase ignition and combustion. In this work, several aspects of horizontal and vertical forest structure were evaluated to understand how spatial complexity influences fire behavior, with a particular emphasis on the transition of a surface fire into tree crowns. I used a combination of spatially explicit field data and a physics-based wildfire model, the Wildland-Urban Interface Fire Dynamics Simulator (WFDS), to deepen our fundamental understanding of fire behavior, inform the design of forest treatments that aim to achieve a variety of ecological and social objectives, and develop hypotheses related to the pattern-process feedbacks that contributed to the maintenance of resilient forests across millennia. Chapter 2 presents a simulation study focused on the relationship between horizontal forest structure and surface to crown heat transfer and crown fire initiation. The results indicated that relative to larger 7- and 19-tree groups, isolated individual trees and 3-tree groups had greater convective cooling and reduced canopy heat flux. Because isolated individuals and 3-tree groups were exposed to less thermal energy, they required a greater surface fireline intensity to initiate torching and had less crown consumption than trees within larger groups. Similarly, I found that increased crown separation distance between trees reduced the net heat flux leading to reduced ignition potential. These findings identify the potential physical mechanisms responsible for supporting the complex forest structures typical of high-frequency fire regimes and may be useful for managers designing fuel hazard reduction and ecological restoration treatments. Chapter 3 extends chapter 2 by investigating how different levels and types of vertical heterogeneity influence crown fire transition and canopy consumption within tree groups. These results show the importance of fuel stratum gap (or canopy base height) on vertical fire propagation, however vertical fire propagation was mediated by the level of horizontal connectivity in the upper crown layers. This suggests that the fuel stratum gap cannot fully characterize the torching hazard. The results also indicate that as the surface fire line intensity increases, the influence of horizontal connectivity on canopy consumption is amplified. At the scale of individual tree groups, the perceived hazard of small, understory trees and vertical fuel continuity may be offset by lower horizontal continuity (or canopy bulk density) within the midstory and overstory crown layers. Chapter 4 compares outcomes from four real-world forest treatments that cover a range of potential treatment approaches to evaluate their impacts of forest spatial pattern and potential fire behavior. My results indicate that restoration treatments created greater vertical and horizontal structural complexity than the fuel hazard reduction treatments but resulted in similar reductions to potential fire severity. However, the restoration treatments did increase the surface fire rate of spread which suggests some potential fire behavior tradeoffs among treatment approaches. Overall, these results suggest the utility of restoration treatments in achieving a wide range of management objectives, including fire hazard reduction, and that they can be used in concert with traditional fuel hazard reduction treatments to reduce landscape scale fire risk. Together this work shows that tree spatial pattern can significantly influence crown fire initiation and canopy consumption through alterations to net heat transfer and feedbacks among closely spaced trees. At the scale of the tree group these results suggest that larger tree groups may sustain higher levels of canopy consumption and mortality as they are easier to ignite and, in cases with small separation between crowns, can sustain horizontal spread resulting in density-depended crown damage. These findings carry over to vertically complex groups where the spatial relationship between small, understory trees and larger, overstory trees has a large impact on the ability of fire to be carried vertically. Further, in these vertically complex groups reducing the density (and/or increasing the horizontal separation) of the overstory trees, resulted in lower rates of crown fuel consumption, therefore, mitigating some of the "laddering" effect caused by the presence of small understory trees. These complex interactions between vertical and horizontal aspects of stand structure were born out in my evaluation of the measured forest treatments, where similar crown fire behavior reductions were observed across various stand structures. Overall, this work shows that forest managers can apply treatments to achieve a wide range of ecological benefits while simultaneously increasing fire resistance and resilience

Recent advances in remote sensing of seasonal snow

Remote sensing offers local, regional and global observations of seasonal snow, providing key information on snowpack processes. This brief review highlights advancements in instrumentation and analysis techniques that have been developed over the past decade. Areas of advancement include improved algorithms for mapping snow-cover extent, snow albedo, snow grain size, snow water equivalent, melt detection and snow depth, as well as new uses of instruments such as multiangular spectroradiometers, scatterometry and lidar. Limitations and synergies of the instruments and techniques are discussed, and remaining challenges such as multisensor mapping, scaling issues, vegetation correction and data assimilation are identified

Climate and more sustainable cities: climate information for improved planning and management of cities (producers/capabilities perspective)

In the last two decades substantial advances have been made in the understanding of the scientific basis of urban climates. These are reviewed here with attention to sustainability of cities, applications that use climate information, and scientific understanding in relation to measurements and modelling. Consideration is given from street (micro) scale to neighbourhood (local) to city and region (meso) scale. Those areas where improvements are needed in the next decade to ensure more sustainable cities are identified. High-priority recommendations are made in the following six strategic areas: observations, data, understanding, modelling, tools and education. These include the need for more operational urban measurement stations and networks; for an international data archive to aid translation of research findings into design tools, along with guidelines for different climate zones and land uses; to develop methods to analyse atmospheric data measured above complex urban surfaces; to improve short-range, high-resolution numerical prediction of weather, air quality and chemical dispersion through improved modelling of the biogeophysical features of the urban land surface; to improve education about urban meteorology; and to encourage communication across scientific disciplines at a range of spatial and temporal scales

Modeling Subgrid Variability of Snow Depth Using the Fokker-Planck Equation Approach

AbstractA physically based subgrid variability model for snow process using the Fokker‐Planck equation (FPE) approach was proposed. This FPE can express the evolution of the probability density function (PDF) of snow depth within a finite area, possibly a grid cell of distributed models or a small basin, whose shape can be irregular. The main advantage of this approach is that it does not rely on a given PDF but dynamically computes the PDF through an advection‐diffusion‐type equation, the FPE, which was derived from point‐scale process‐based governing equations. Snow depth was treated as a random variable, while the snow redistribution and snowmelt rate were treated as the sources of stochasticity. The main challenge in solving this FPE is evaluating the time‐space covariances appearing in the diffusion coefficient. In this study, approximations to evaluate the covariance terms, accounting for snowmelt and snow redistribution, were proposed. The simulated results of the FPE model were validated by the measured time series of snow depth at one site and the spatial distributions of snow depth measured by ground penetrating radar and airborne light detection and ranging (Lidar). It was shown that the point‐observed snow depth fell within the simulated range during most of the 2‐year study period. The simulated PDFs of snow depth within the study area were similar to the observed PDFs of snow depth by ground penetrating radar and Lidar. In summary, these results demonstrate the efficacy of the proposed FPE model representing the subgrid variability of snow depth

Peak-summer energy and carbon fluxes on a thawing permafrost site

We present measurements of surface fluxes taken between 7 July and 6 August 2017, on a palsa mire near the Iškoras mountain in Finnmark, northern Norway. Palsa mires are a particular landform found at the edge of the discontinuous permafrost zone, where mean annual temperatures are close to 0 °C and climate change is expected to have a high impact. Turbulent fluxes of sensible heat, latent heat and carbon dioxide were measured with the eddy-covariance (EC) method, while complementary energy balance data was provided by a net radiometer and two soil heat flux plates. The raw turbulence data was processed by the validated TK3 software package, which applies the plausability tests, corrections and quality controls needed for reliable flux calculations. Through a footprint analysis we found the average turbulent fetch area to overlap well with our ecosystem of interest, in that only 20 % of the footprint climatology was outside the palsa mire. However, a greater carbon uptake was observed during northerly winds than otherwise, which suggests that the more vegetated area to the north of the palsa mire also influenced our flux measurements. Overall, our results are similar to those of other studies from the growing season at sub-Arctic sites. The mean daytime Bowen ratio was 74 %, which is typical for high-latitude wetlands in summertime. The soil heat flux was positive most of the time, and from our cumulative flux estimates we found a large soil heat uptake during the campaign, which is characteristic for permafrost regions during the warm season. However, the average flux from the upper sensor at 10 cm was only 8 % of the net radiation. This is in general less than what other permafrost studies have found for the ground heat flux, likely due to a change in heat storage above the 10 cm level. The average net ecosystem exchange of carbon dioxide during the campaign was –1.1 μmol/m2s, which indicates carbon uptake and compares well to what has been reported in other studies from similar sites in summertime. Differences in carbon budgets between sub-Arctic ecosystems seem to be associated with the vegetation cover. A certain long-term increase in carbon flux amplitude was found, likely related to vegetation growth. We were not able to verify the surface energy balance equation with our measurements, but using longwave radiation data we managed to estimate the true ground heat flux at the surface. This gave a better, though not perfect, balance. Our ogive test suggested that a significant fraction of the turbulent fluxes were inadequately sampled with a block averaging period of only 30 min, which also contributed to the observed imbalance in surface heat fluxes.Masteroppgåve i meteorologi og oseanografiMAMN-GEOFGEOF39

An approach for modelling snowcover ablation and snowmelt runoff in cold region environments

Reliable hydrological model simulations are the result of numerous complex interactions among hydrological inputs, landscape properties, and initial conditions. Determination of the effects of these factors is one of the main challenges in hydrological modelling. This situation becomes even more difficult in cold regions due to the ungauged nature of subarctic and arctic environments. This research work is an attempt to apply a new approach for modelling snowcover ablation and snowmelt runoff in complex subarctic environments with limited data while retaining integrity in the process representations. The modelling strategy is based on the incorporation of both detailed process understanding and inputs along with information gained from observations of basin-wide streamflow phenomenon; essentially a combination of deductive and inductive approaches. The study was conducted in the Wolf Creek Research Basin, Yukon Territory, using three models, a small-scale physically based hydrological model, a land surface scheme, and a land surface hydrological model. The spatial representation was based on previous research studies and observations, and was accomplished by incorporating landscape units, defined according to topography and vegetation, as the spatial model elements. Comparisons between distributed and aggregated modelling approaches showed that simulations incorporating distributed initial snowcover and corrected solar radiation were able to properly simulate snowcover ablation and snowmelt runoff whereas the aggregated modelling approaches were unable to represent the differential snowmelt rates and complex snowmelt runoff dynamics. Similarly, the inclusion of spatially distributed information in a land surface scheme clearly improved simulations of snowcover ablation. Application of the same modelling approach at a larger scale using the same landscape based parameterisation showed satisfactory results in simulating snowcover ablation and snowmelt runoff with minimal calibration. Verification of this approach in an arctic basin illustrated that landscape based parameters are a feasible regionalisation framework for distributed and physically based models. In summary, the proposed modelling philosophy, based on the combination of an inductive and deductive reasoning, is a suitable strategy for reliable predictions of snowcover ablation and snowmelt runoff in cold regions and complex environments