The spatial scale dependence of water vapor variability inferred from observations from a very tall tower

Recent studies have established that atmospheric water vapor fields exhibit spatial spectra that take the form of power laws and hence can be compactly characterized by scaling exponents. The power law scaling exponents have been shown to exhibit substantial vertical variability. In this work, Taylor's frozen turbulence hypothesis is used to infer the first-order spatial structure function and generalized detrended fluctuation function scaling exponents for scales between 1 km and 100 km. Both methods are used to estimate the Hurst exponent (H) using 10 Hz time series of water vapor measured at 396 m altitude from an Ameriflux tower in Wisconsin. Due to the diurnal cycle in the boundary layer height at the 396 m observational level, H may be estimated for both the daytime convective mixed layer and the nocturnal residual layer. Values of H ≈ 1/3 are obtained for the convective mixed layer, while values of H > 1/2 apply in the nocturnal residual layer. The results are shown to be remarkably consistent with a similar analysis from satellite-based observations as reported in Pressel and Collins (2012)

Space‐Scale Resolved Surface Fluxes Across a Heterogeneous, Mid‐Latitude Forested Landscape

The Earth\u27s surface is heterogeneous at multiple scales owing to spatial variability in various properties. The atmospheric responses to these heterogeneities through fluxes of energy, water, carbon, and other scalars are scale-dependent and nonlinear. Although these exchanges can be measured using the eddy covariance technique, widely used tower-based measurement approaches suffer from spectral losses in lower frequencies when using typical averaging times. However, spatially resolved measurements such as airborne eddy covariance measurements can detect such larger scale (meso-β, meso-γ) transport. To evaluate the prevalence and magnitude of these flux contributions, we applied wavelet analysis to airborne flux measurements over a heterogeneous mid-latitude forested landscape, interspersed with open water bodies and wetlands. The measurements were made during the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors intensive field campaign. We ask, how do spatial scales of surface-atmosphere fluxes vary over heterogeneous surfaces across the day and across seasons? Measured fluxes were separated into smaller-scale turbulent and larger-scale mesoscale contributions. We found significant mesoscale contributions to sensible and latent heat fluxes through summer to autumn which would not be resolved in single-point tower measurements through traditional time-domain half-hourly Reynolds decomposition. We report scale-resolved flux transitions associated with seasonal and diurnal changes of the heterogeneous study domain. This study adds to our understanding of surface-atmospheric interactions over unstructured heterogeneities and can help inform multi-scale model-data integration of weather and climate models at a sub-grid scale

Persistent reduced ecosystem respiration after insect disturbance in high elevation forests

Amid a worldwide increase in tree mortality, mountain pine beetles (Dendroctonus ponderosae Hopkins) have led to the death of billions of trees from Mexico to Alaska since 2000. This is predicted to have important carbon, water and energy balance feedbacks on the Earth system. Counter to current projections, we show that on a decadal scale, tree mortality causes no increase in ecosystem respiration from scales of several square metres up to an 84 km2 valley. Rather, we found comparable declines in both gross primary productivity and respiration suggesting little change in net flux, with a transitory recovery of respiration 6–7 years after mortality associated with increased incorporation of leaf litter C into soil organic matter, followed by further decline in years 8–10. The mechanism of the impact of tree mortality caused by these biotic disturbances is consistent with reduced input rather than increased output of carbon

eddy4R 0.2.0: a DevOps model for community-extensible processing and analysis of eddy-covariance data based on R, Git, Docker, and HDF5

Large differences in instrumentation, site setup, data format, and operating system stymie the adoption of a universal computational environment for processing and analyzing eddy-covariance (EC) data. This results in limited software applicability and extensibility in addition to often substantial inconsistencies in flux estimates. Addressing these concerns, this paper presents the systematic development of portable, reproducible, and extensible EC software achieved by adopting a development and systems operation (DevOps) approach. This software development model is used for the creation of the eddy4R family of EC code packages in the open-source R language for statistical computing. These packages are community developed, iterated via the Git distributed version control system, and wrapped into a portable and reproducible Docker filesystem that is independent of the underlying host operating system. The HDF5 hierarchical data format then provides a streamlined mechanism for highly compressed and fully self-documented data ingest and output. The usefulness of the DevOps approach was evaluated for three test applications. First, the resultant EC processing software was used to analyze standard flux tower data from the first EC instruments installed at a National Ecological Observatory (NEON) field site. Second, through an aircraft test application, we demonstrate the modular extensibility of eddy4R to analyze EC data from other platforms. Third, an intercomparison with commercial-grade software showed excellent agreement (R2  =  1.0 for CO2 flux). In conjunction with this study, a Docker image containing the first two eddy4R packages and an executable example workflow, as well as first NEON EC data products are released publicly. We conclude by describing the work remaining to arrive at the automated generation of science-grade EC fluxes and benefits to the science community at large. This software development model is applicable beyond EC and more generally builds the capacity to deploy complex algorithms developed by scientists in an efficient and scalable manner. In addition, modularity permits meeting project milestones while retaining extensibility with time

Novel approach to observing system simulation experiments improves information gain of surface-atmosphere field measurements

The observing system design of multidisciplinary field measurements involves a variety of considerations on logistics, safety, and science objectives. Typically, this is done based on investigator intuition and designs of prior field measurements. However, there is potential for considerable increases in efficiency, safety, and scientific success by integrating numerical simulations in the design process. Here, we present a novel numerical simulation-environmental response function (NS-ERF) approach to observing system simulation experiments that aids surface-atmosphere synthesis at the interface of mesoscale and microscale meteorology. In a case study we demonstrate application of the NS-ERF approach to optimize the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 (CHEESEHEAD19). During CHEESEHEAD19 pre-field simulation experiments, we considered the placement of 20 eddy covariance flux towers, operations for 72h of low-altitude flux aircraft measurements, and integration of various remote sensing data products. A 2h high-resolution large eddy simulation created a cloud-free virtual atmosphere for surface and meteorological conditions characteristic of the field campaign domain and period. To explore two specific design hypotheses we super-sampled this virtual atmosphere as observed by 13 different yet simultaneous observing system designs consisting of virtual ground, airborne, and satellite observations. We then analyzed these virtual observations through ERFs to yield an optimal aircraft flight strategy for augmenting a stratified random flux tower network in combination with satellite retrievals. We demonstrate how the novel NS-ERF approach doubled CHEESEHEAD19's potential to explore energy balance closure and spatial patterning science objectives while substantially simplifying logistics. Owing to its modular extensibility, NS-ERF lends itself to optimizing observing system designs also for natural climate solutions, emission inventory validation, urban air quality, industry leak detection, and multi-species applications, among other use cases. © 2021 Stefan Metzger et al

Observations of ¹⁴CO₂ in ecosystem respiration from a temperate deciduous forest in Northern Wisconsin

The ¹⁴CO₂ composition of plant and soil respiration can be used to determine the residence time of photosynthetically fixed carbon before it is released back to the atmosphere. To estimate the residence time of actively cycled carbon in a temperate forest, we employed two approaches for estimating the Δ¹⁴CO₂ of ecosystem respiration (Δ¹⁴C-R[subscript eco]) at the Willow Creek AmeriFlux site in Northern Wisconsin, USA. Our first approach was to construct nighttime Keeling plots from subcanopy profiles of Δ¹⁴CO₂ and CO₂, providing estimates of Δ¹⁴C-R[subscript eco] of 121.7‰ in June and 42.0‰ in August 2012. These measurements are likely dominated by soil fluxes due to proximity to the ground level. Our second approach utilized samples taken over 20 months within the forest canopy and from 396 m above ground level at the nearby LEF NOAA tall tower site (Park Falls, WI). In this canopy-minus-background approach we employed a mixing model described by Miller and Tans (2003) for estimating isotopic sources by subtracting time-varying background conditions. For the period from May 2011 to December 2012 the estimated Δ¹⁴C-R[subscript eco] using the Miller-Tans model was 76.8‰. Together, these Δ¹⁴C-R[subscript eco] values represent mean R[subscript eco] carbon ages of approximately 1–19 years. We also found that heterotrophic soil-respired Δ¹⁴C at Willow Creek was 5–38‰ higher (i.e., 1–10 years older) than predicted by the Carnegie-Ames-Stanford Approach global biosphere carbon model for the 1 × 1 pixel nearest to the site. This study provides much needed observational constraints of ecosystem carbon residence times, which are a major source of uncertainty in terrestrial carbon cycle models.This is the publisher’s final pdf. The published article is copyrighted by American Geophysical Union and can be found at: http://agupubs.onlinelibrary.wiley.com/agu/jgr/journal/10.1002/%28ISSN%292169-8961/Keywords: AmeriFlux, respiration, Keeling plot, radiocarbonKeywords: AmeriFlux, respiration, Keeling plot, radiocarbo

Impact of forest plantation on methane emissions from tropical peatland

Tropical peatlands are a known source of methane (CH4) to the atmosphere, but their contribution to atmospheric CH4 is poorly constrained. Since the 1980s, extensive areas of the peatlands in Southeast Asia have experienced land‐cover change to smallholder agriculture and forest plantations. This land‐cover change generally involves lowering of groundwater level (GWL), as well as modification of vegetation type, both of which potentially influence CH4 emissions. We measured CH4 exchanges at the landscape scale using eddy covariance towers over two land‐cover types in tropical peatland in Sumatra, Indonesia: (a) a natural forest and (b) an Acacia crassicarpa plantation. Annual CH4 exchanges over the natural forest (9.1 ± 0.9 g CH4 m−2 year−1) were around twice as high as those of the Acacia plantation (4.7 ± 1.5 g CH4 m−2 year−1). Results highlight that tropical peatlands are significant CH4 sources, and probably have a greater impact on global atmospheric CH4 concentrations than previously thought. Observations showed a clear diurnal variation in CH4 exchange over the natural forest where the GWL was higher than 40 cm below the ground surface. The diurnal variation in CH4 exchanges was strongly correlated with associated changes in the canopy conductance to water vapor, photosynthetic photon flux density, vapor pressure deficit, and air temperature. The absence of a comparable diurnal pattern in CH4 exchange over the Acacia plantation may be the result of the GWL being consistently below the root zone. Our results, which are among the first eddy covariance CH4 exchange data reported for any tropical peatland, should help to reduce the uncertainty in the estimation of CH4 emissions from a globally important ecosystem, provide a more complete estimate of the impact of land‐cover change on tropical peat, and develop science‐based peatland management practices that help to minimize greenhouse gas emissions

Drought and Waterlogging Stress Regimes in Northern Peatlands Detected Through Satellite Retrieved Solar-Induced Chlorophyll Fluorescence

The water table depth (WTD) in peatlands determines the soil carbon decomposition rate and influences vegetation growth, hence the above-ground carbon assimilation. Here, we used satellite-observed Solar-Induced chlorophyll Fluorescence (SIF) as a proxy of Gross Primary Production (GPP) to investigate water-related vegetation stress over northern peatlands. A linear model with interaction effects was used to relate short- and long-term anomalies in SIF with WTD anomalies and the absolute WTD. Most locations showed the occurrence of drought and waterlogging stress though regions with exclusively waterlogging or drought stress were also detected. As a spatial median, minimal water-related vegetation stress was found for a WTD of -0.22 m (short-term) and -0.20 m (long-term) (+/- 0.01 m, 95% confidence interval of statistical uncertainty). The stress response observed with SIF is supported by an analysis of in situ GPP data. Our findings provide insight into how changes in WTD of northern peatlands could affect GPP under climate change.Water table depth is an important variable influencing the carbon cycle and vegetation growth in northern peatlands. In this paper, the impact of changing wetness conditions on vegetation growth over peatlands was studied through satellite measurements of solar-induced fluorescence (SIF), which is a radiation signal emitted by vegetation during photosynthesis. Previous studies over ecosystems on mineral soil, that is, not over peatland, suggested a response of SIF to drought conditions. In our study, it was shown that peatland vegetation experiences moisture-related growth stress under both very wet and very dry conditions, which might reduce the photosynthesis efficiency and the ability to capture and store CO2. Stress due to drought conditions was detected for peatlands in the south of the Western Siberian Lowlands and the Boreal Plains. Stress due to prolonged wet conditions occurred for example, in the north of the Western Siberian Lowlands and the north of the Hudson Bay Lowlands.Spaceborne Solar-Induced Fluorescence (SIF) data was used to analyze soil moisture-related vegetation stress regimes in northern peatlandsFor most locations, waterlogging as well as drought stress regimes occurred and alternated depending on peatland water level dynamicsThe SIF-based stress response observations are supported by in situ data of Gross Primary Productio

Characterizing the diurnal patterns of errors in the prediction of evapotranspiration by several land‐surface models: An NACP analysis

Land‐surface models use different formulations of stomatal conductance and plant hydraulics, and it is unclear which type of model best matches the observed surface‐atmosphere water flux. We use the North American Carbon Program data set of latent heat flux (LE) measurements from 25 sites and predictions from 9 models to evaluate models' ability to resolve subdaily dynamics of transpiration. Despite overall good forecast at the seasonal scale, the models have difficulty resolving the dynamics of intradaily hysteresis. The majority of models tend to underestimate LE in the prenoon hours and overestimate in the evening. We hypothesize that this is a result of unresolved afternoon stomatal closure due to hydrodynamic stresses. Although no model or stomata parameterization was consistently best or worst in terms of ability to predict LE, errors in model‐simulated LE were consistently largest and most variable when soil moisture was moderate and vapor pressure deficit was moderate to limiting. Nearly all models demonstrate a tendency to underestimate the degree of maximum hysteresis which, across all sites studied, is most pronounced during moisture‐limited conditions. These diurnal error patterns are consistent with models' diminished ability to accurately simulate the natural hysteresis of transpiration. We propose that the lack of representation of plant hydrodynamics is, in part, responsible for these error patterns. Key Points Land‐surface models produce subdaily patterns of latent heat flux error Error patterns are characterized by the stomatal conductance formulation used Current models lack a mechanism to simulate hysteretic transpirationPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108341/1/jgrg20246.pd