skip to main content


Title: Upscaling surface energy fluxes over the North Slope of Alaska using airborne eddy-covariance measurements and environmental response functions
Abstract. The objective of this study was to upscale airborne flux measurements ofsensible heat and latent heat and to develop high-resolution flux maps. Inorder to support the evaluation of coupled atmospheric–land-surface models weinvestigated spatial patterns of energy fluxes in relation to land-surfaceproperties. We used airborne eddy-covariance measurements acquired by the Polar 5research aircraft in June–July 2012 to analyze surface fluxes.Footprint-weighted surface properties were then related to 21 529 sensibleheat flux observations and 25 608 latent heat flux observations using bothremote sensing and modeled data. A boosted regression tree technique wasused to estimate environmental response functions between spatially andtemporally resolved flux observations and corresponding biophysical andmeteorological drivers. In order to improve the spatial coverage and spatialrepresentativeness of energy fluxes we used relationships extracted acrossheterogeneous Arctic landscapes to infer high-resolution surface energy fluxmaps, thus directly upscaling the observational data. These maps of projectedsensible heat and latent heat fluxes were used to assess energy partitioningin northern ecosystems and to determine the dominant energy exchangeprocesses in permafrost areas. This allowed us to estimate energy fluxes forspecific types of land cover, taking into account meteorological conditions.Airborne and modeled fluxes were then compared with measurements from aneddy-covariance tower near Atqasuk. Our results are an important contribution for the advanced, scale-dependentquantification of surface energy fluxes and they provide new insights into theprocesses affecting these fluxes for the main vegetation types inhigh-latitude permafrost areas.  more » « less
Award ID(s):
1724433
NSF-PAR ID:
10376522
Author(s) / Creator(s):
; ; ; ; ;
Date Published:
Journal Name:
Atmospheric Chemistry and Physics
Volume:
18
Issue:
13
ISSN:
1680-7324
Page Range / eLocation ID:
10007 to 10023
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract

    Detailed assessment of small‐scale heterogeneity in local surface water balance is essential to accurate estimation of evapotranspiration in semiarid climates. However, meteorological approaches are often impractical to implement in sites with sparse and diverse vegetation composition, especially with seasonally variable leaf canopy features. Ground‐based infrared thermometry (TIR) provides spatially and temporally continuous resolution of surface skin temperature that can be directly related to the land surface energy balance. We made repeated measurements with a portable TIR camera to capture seasonal replicates for patch scale heat images for four sagebrush communities. The heat images near peak foliage and near the end of the growing season were compared by computation of surface energy fluxes from TIR sensing to surface energy balance (SEB) and Bowen ratio (BR). Estimates of sensible (H) and latent heat flux (LE) were evaluated with eddy covariance measurements to disaggregate the expression of seasonal phenology of sagebrush species across wetness and elevation. Estimations showed reasonable agreement with ground‐basedLEobservations for most cases (r2 = 0.59–0.76 for SEB and 0.22–0.72 for BR; root mean squared error = 73.4–106.4 W m−2for SEB and 109.9–204.0 W m−2for BR). Predictability declined as the fraction of senescent foliage increased in dry conditions. The field trials suggest the methods have the potential for monitoring land surface energy fluxes and plant health at a very fine spatial scale. The ability to partition heat fluxes from various plant communities over a range of moisture availability will provide valuable information associated with the consumptive water use and phenological processes in the semiarid West.

     
    more » « less
  2. Abstract

    The eddy covariance method is widely used to investigate fluxes of energy, water, and carbon dioxide at landscape scales, providing important information on how ecological systems function. Flux measurements quantify ecosystem responses to environmental perturbations and management strategies, including nature‐based climate‐change mitigation measures. However, due to the high cost of conventional instrumentation, most eddy covariance studies employ a single system, limiting spatial representation to the flux footprint. Insufficient replication may be limiting our understanding of ecosystem behavior. To address this limitation, we deployed eight lower‐cost eddy covariance systems in two clusters around two conventional eddy covariance systems in the Chihuahuan Desert of North America for a period of 2 years. These dryland settings characterized by large temperature variations and relatively low carbon dioxide fluxes represented a challenging setting for eddy covariance. We found very good closure of energy and water balance across all systems (within ±9% of unity). We found very good correspondence between the lower‐cost and conventional systems' fluxes of sensible heat (with concordance correlation coefficient (CCC) of ≥0.87), latent energy (evapotranspiration; CCC ≥ 0.89), and useful correspondence in the net ecosystem exchange ((NEE); with CCC ≥ 0.4) at the daily temporal resolution. Relative to the conventional systems, the low‐frequency systems were characterized by a higher level of random error, particularly in the NEE fluxes. Lower‐cost systems can enable wider deployment affording better replication and sampling of spatiotemporal variability at the expense of greater measurement noise that might be limiting for certain applications. Replicated eddy covariance observations may be useful when addressing gaps in the existing monitoring of critical and underrepresented ecosystems and for measuring areas larger than a single flux footprint.

     
    more » « less
  3. Eddy covariance measurements quantify the magnitude and temporal variability of land-atmosphere exchanges of water, heat, and carbon dioxide (CO 2 ) among others. However, they also carry information regarding the influence of spatial heterogeneity within the flux footprint, the temporally dynamic source/sink area that contributes to the measured fluxes. A 25 m tall eddy covariance flux tower in Central Illinois, USA, a region where drastic seasonal land cover changes from intensive agriculture of maize and soybean occur, provides a unique setting to explore how the organized heterogeneity of row crop agriculture contributes to observations of land-atmosphere exchange. We characterize the effects of this heterogeneity on latent heat ( LE ), sensible heat ( H ), and CO 2 fluxes ( F c ) using a combined flux footprint and eco-hydrological modeling approach. We estimate the relative contribution of each crop type resulting from the structured spatial organization of the land cover to the observed fluxes from April 2016 to April 2019. We present the concept of a fetch rose, which represents the frequency of the location and length of the prevalent upwind distance contributing to the observations. The combined action of hydroclimatological drivers and land cover heterogeneity within the dynamic flux footprint explain interannual flux variations. We find that smaller flux footprints associated with unstable conditions are more likely to be dominated by a single crop type, but both crops typically influence any given flux measurement. Meanwhile, our ecohydrological modeling suggests that land cover heterogeneity leads to a greater than 10% difference in flux magnitudes for most time windows relative to an assumption of equally distributed crop types. This study shows how the observed flux magnitudes and variability depend on the organized land cover heterogeneity and is extensible to other intensively managed or otherwise heterogeneous landscapes. 
    more » « less
  4. Abstract

    Climate change is rapidly altering composition, structure, and functioning of the boreal biome, across North America often broadly categorized into ecoregions. The resulting complex changes in different ecoregions present a challenge for efforts to accurately simulate carbon dioxide (CO2) and energy exchanges between boreal forests and the atmosphere with terrestrial ecosystem models (TEMs). Eddy covariance measurements provide valuable information for evaluating the performance of TEMs and guiding their development. Here, we compiled a boreal forest model benchmarking dataset for North America by harmonizing eddy covariance and supporting measurements from eight black spruce (Picea mariana)-dominated, mature forest stands. The eight forest stands, located in six boreal ecoregions of North America, differ in stand characteristics, disturbance history, climate, permafrost conditions and soil properties. By compiling various data streams, the benchmarking dataset comprises data to parameterize, force, and evaluate TEMs. Specifically, it includes half-hourly, gap-filled meteorological forcing data, ancillary data essential for model parameterization, and half-hourly, gap-filled or partitioned component flux data on CO2(net ecosystem production, gross primary production [GPP], and ecosystem respiration [ER]) and energy (latent [LE] and sensible heat [H]) and their daily aggregates screened based on half-hourly gap-filling quality criteria. We present a case study with the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) to: (1) demonstrate the utility of our dataset to benchmark TEMs and (2) provide guidance for model development and refinement. Model skill was evaluated using several statistical metrics and further examined through the flux responses to their environmental controls. Our results suggest that CLASSIC tended to overestimate GPP and ER among all stands. Model performance regarding the energy fluxes (i.e., LE and H) varied greatly among the stands and exhibited a moderate correlation with latitude. We identified strong relationships between simulated fluxes and their environmental controls except for H, thus highlighting current strengths and limitations of CLASSIC.

     
    more » « less
  5. null (Ed.)
    Abstract. Flux measurements of nitrogen oxides (NOx) were made over London usingairborne eddy covariance from a low-flying aircraft. Seven low-altitude flights were conducted over Greater London, performing multiple overpasses across the city during eight days in July 2014. NOx fluxes across theGreater London region (GLR) exhibited high heterogeneity and strong diurnalvariability, with central areas responsible for the highest emission rates(20–30 mg m−2 h−1). Other high-emission areas included the M25 orbital motorway. The complexity of London's emission characteristics makes it challenging to pinpoint single emissions sources definitively usingairborne measurements. Multiple sources, including road transport andresidential, commercial and industrial combustion sources, are all likely to contribute to measured fluxes. Measured flux estimates were compared toscaled National Atmospheric Emissions Inventory (NAEI) estimates, accountingfor monthly, daily and hourly variability. Significant differences were found between the flux-driven emissions and the NAEI estimates acrossGreater London, with measured values up to 2 times higher in Central London than those predicted by the inventory. To overcome the limitations ofusing the national inventory to contextualise measured fluxes, we usedphysics-guided flux data fusion to train environmental response functions(ERFs) between measured flux and environmental drivers (meteorological and surface). The aim was to generate time-of-day emission surfaces usingcalculated ERF relationships for the entire GLR; 98 % spatial coverage was achieved across the GLR at 400 m2 spatial resolution. All flight legprojections showed substantial heterogeneity across the domain, with highemissions emanating from Central London and major road infrastructure. Thediurnal emission structure of the GLR was also investigated, through ERF,with the morning rush hour distinguished from lower emissions during the early afternoon. Overall, the integration of airborne fluxes with anERF-driven strategy enabled the first independent generation of surfaceNOx emissions, at high resolution using an eddy-covariance approach,for an entire city region. 
    more » « less