Influence of Tundra Polygon Type and Climate Variability on CO\u3csub\u3e2\u3c/sub\u3e and CH\u3csub\u3e4\u3c/sub\u3e Fluxes Near Utqiagvik, Alaska

Arctic tundra has the potential to generate significant climate feedbacks, but spatial complexity makes it difficult to quantify the impacts of climate on ecosystem-atmosphere fluxes, particularly in polygonal tundra comprising wetter and drier polygon types on the scale of tens of meters. We measured CO2, CH4, and energy fluxes using eddy covariance for 7 yr (April to November, 2013–2019) in polygonal tundra near Utqiagvik, Alaska. This period saw the earliest snowmelt, latest snow accumulation, and hottest summer on record. To estimate fluxes by polygon type, we combined a polygon classification with a flux-footprint model. Methane fluxes were highest in the summer months but were also large during freeze-up and increased with the warming trend in August–November temperatures. While CO2 respiration had a consistent, exponential relationship with temperature, net ecosystem exchange was more variable among years. CO2 and CH4 exchange (June–September) ranged between −0.83 (Standard error [SE] = 0.03) and −1.32 (SE = 0.04) μmol m−2 s−1 and 13.92 (SE = 0.26)—23.42 (SE = 0.45) nmol m−2 s−1, respectively, and varied interannually (p ≤ 0.05). The maximum-influence method effectively attributed fluxes to polygon types. Areas dominated by lowcentered polygons had higher CO2 fluxes except in 2016–2017. Methane fluxes were highest in low-centered polygons 2013–2015 and in flat-centered polygons in subsequent years, possibly due to increasing temperature and precipitation. Sensible and latent heat fluxes also varied significantly among polygon types. Accurate characterization of Arctic fluxes and their climate dependencies requires spatial disaggregation and long term observations. Plain Language Summary We measured carbon dioxide and methane fluxes for 7 yr (April to November, 2013–2019) in polygonal tundra near Utqiagvik (Barrow), Alaska using eddy covariance (EC). The EC method provides the measurements of vertical flux of transported air parcels by correlation of the fluctuations in carbon dioxide or methane concentration with fluctuations in the vertical wind speed. The ice wedge polygonal tundra area is covered by ponds, drained lake basins, and wetter and drier polygon types on the scale of tens of meters across. This period saw the earliest snowmelt, latest snow accumulation date, and hottest summer on record. To estimate fluxes by polygon type, we combined a polygon classification with a flux-footprint model. The model represents the field of view of the EC system and allows the user to extract the location of the peak contribution. The site was a net carbon sink between June and September in each of the seven years. Areas dominated by low-centered polygons had higher carbon dioxide fluxes except in 2016–2017, while methane fluxes were highest in low-centered polygons 2013–2015 and in flat-centered polygons in subsequent years. This is possibly due to increasing temperature and precipitation. Not only were methane fluxes highest in the summer months but also large during freeze-up and increased with the warming trend in August–November temperatures

Portable Flux Tower Deployments Field Campaign Report

Contents Acronyms and Abbreviations...................................................................... iii 1.0 Summary ....................................................... 1 2.0 Results ........................................... 1 3.0 Publications and References ................................................. 2 4.0 Lessons Learned ....................................................................

A Portable Eddy Covariance System for the Measurement of Ecosystem–Atmosphere Exchange of CO2, Water Vapor, and Energy

To facilitate the study of flux heterogeneity within a region, the authors have designed and field-tested a portable eddy covariance system to measure exchange of CO2, water vapor, and energy between the land surface and the atmosphere. The combination of instrumentation used in this system allows high precision flux measurements without requiring on-site infrastructure such as prepositioned towers or line power. In addition, the system contains sensors to measure a suit of soil, climatic, and energy-related parameters that are needed to quality control the fluxes and to characterize the flux footprint. The physical design and instrument packaging used in the system allows for simple transport (fits in a standard minivan) and for rapid deployment with a minimal number of field personnel (usually less than a day for one person). The power requirement for the entire system (instruments and data loggers) is less than 35 W, which is provided by a companion solar power system. Side-by-side field comparisons between this system and two permanent AmeriFlux sites and between the roving AmeriFlux intercomparison system are described here. Results of these comparisons indicate that the portable system is capable of absolute flux resolutions of about 61.2 mmol m22 s21 for CO2, 615 W m22 for LE, 67 W m22 for H, and 60.06 m s21 for u* between any given 30-min averaging periods. It is also found that, compared to a permanent Ameriflux site, the relative accuracy of this flux estimates is between 1% and 7%. Based on these results, it is concluded that this portable system is capable of making ecosystem flux measurements with an accuracy and precision comparable to most permanent AmeriFlux systems

Annual, seasonal, and diel surface energy partitioning in the semiarid Sand Hills of Nebraska, USA

Study Region: The Nebraska Sand Hills consisting of four major land cover types: (1) lakes and wetlands (∼5% for both), (2) subirrigated meadows (∼10%), (3) dry valleys (∼20%), and (4) upland dunes (∼65%). Study Focus: Examination of surface energy and water balances on multiple temporal scales with primary focus on latent heat flux (λE), and evapotranspiration (ET), to gain a better understanding of the annual, seasonal, and diel properties of surface energy partitioning among different Sand Hills ecosystems to improve regional water resource management. New Hydrological Insights for the Region: Based on surface energy and water balance measurements using Bowen ratio energy balance systems at three locations during 2004, we find a strong spatial gradient between sites in latent (λE) and sensible (H) heat flux due to differences in topography, soils, and plant community composition on all timescales. Seasonally, all land covers show the greatest λE in summer. Our results show that subirrigated meadows, dry valleys, and upland dunes allocate roughly 81%, 50%, and 41% of available energy to λE, respectively, during the growing season. The subirrigated meadow was the only cover type where cumulative annual ET surpassed cumulative annual precipitation (i.e. net loss of water to the atmosphere). Therefore, the dry valleys and upland dunes are where net groundwater recharge to the High Plains Aquifer is occurring

Downwind Odor Predictions from Four Swine Finishing Barns Using CALPUFF

A collaborative research effort by several institutions is investigating odor emissions from swine production facilities, and the impacts of those emissions on farm neighbours. Trained human receptors were used to measure the downwind odor concentrations from four tunnel ventilated swine barns near Story City, Iowa. Twenty-six measurement events were conducted between June and November 2004 and modeled using a specially coded short time-step version of CALPUFF to predict short time step durations. Source emission measurements and extensive meteorological data were collected along with ambient olfactometry analysis using the Nasal Ranger™ device (St. Croix Sensory, St. Paul MN). Approximately 64% of measured odor generally falls within the range of modeled values. Analysis of measured odor concentration and corresponding meteorology indicate that maximum ambient odor impacts occur with lower ambient temperature during non-turbulent conditions. Analysis of the data set did not yield a strong relationship directly (R2=0.33), but a regression analysis indicated that the modified CALPUFF model yielded a slope or scaling factor of 0.99, indicating overall a good relationship between model and observed. However, when the data is tested with the Spearman’s rank correlation coefficient an rs of 0.17 was calculated, indicating a poor rank correlation and was not significant (p=0.05). Statistical analysis is inconclusive as to whether the results have bias, but indicate large error in the results. Given that there were no scaling or peak to mean ratio adjustments to the model predictions, the results are very promising for predicting odors using CALPUFF

Modeling Odor Dispersion From a Swine Facility Using AERMOD

Meteorological conditions, odor emissions, and ambient odor levels at a four-barn, swine finishing facility in Iowa were measured in the summer and fall of 2004. This paper compares ambient odor levels measured using a Nasal Ranger® compared to those predicted by AERMOD, a relatively new air dispersion model. Scaling factors needed to adjust predicted odor levels to those observed ranged from 1.66 to 3.12, depending on the source configuration used by the model. Predicted odors levels from the point source configuration required the smallest scaling factor (1.66) and accounted for the greatest percentage of variability in the data when compared to Nasal Ranger readings

Ground Truthing CALPUFF and AERMOD for Odor Dispersion from Swine Barns using Ambient Odor Assessment Techniques

A collaborative research effort by several institutions investigated the dispersion of odors from a swine production facility. Trained human receptors measured downwind odor concentrations from four tunnel-ventilated swine finishing barns near Story City, Iowa, during twenty measurement events conducted between June and November 2004. Odor concentrations were modeled for short time steps using CALPUFF and AERMOD atmospheric dispersion models to compare predicted and measured odor levels. Source emission measurements and extensive micrometeorological data were collected along with ambient odor measurements using the Nasal Ranger® device (St. Croix Sensory, St. Paul MN), Mask Scentometer, odor intensity ratings, and air sample analysis by dynamic triangular forced-choice olfactometry (DTFCO). AERMOD predictions fit the odor measurements slightly better than CALPUFF with predicted concentrations being about half those predicted by CALPUFF. The Mask Scentometer and Nasal Ranger® measurements related best to the dispersion model output, and scaling factors of 3.0 for CALPUFF and 2.4 for AERMOD suggested for the Nasal Ranger® and 0.5 for the Mask Scentometer (both models). Measurements obtained using the Nasal Ranger®, Mask Scentometer, and odor intensity ratings correlated well to each other, had the strongest linear relationships, and provided slopes (measured: modeled) closest to 1.0. Converting intensity ratings to a dilution to threshold concentration did not correlate and relate as well, and this method was deemed less desirable for ambient odor assessment. Collection of ambient air samples for analysis in a olfactometry laboratory displayed poor correlations with other methods and should not be used to assess ambient odors

Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites

Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 103 to 107 m2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applications and to provide general guidance for data use

Robust estimates of soil moisture and latent heat flux coupling strength obtained from triple collocation

Land surface models (LSMs) are often applied to predict the one-way coupling strength between surface soil moisture (SM) and latent heat (LH) flux. However, the ability of LSMs to accurately represent such coupling has not been adequately established. Likewise, the estimation of SM/LH coupling strength using ground-based observational data is potentially compromised by the impact of independent SM and LH measurements errors. Here we apply a new statistical technique to acquire estimates of one-way SM/LH coupling strength which are nonbiased in the presence of random error using a triple collocation approach based on leveraging the simultaneous availability of independent SM and LH estimates acquired from (1) LSMs, (2) satellite remote sensing, and (3) ground-based observations. Results suggest that LSMs do not generally overestimate the strength of one-way surface SM/LH coupling

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible. Supplement file (88 pp) attached below