Spatial variability of greenhouse gas fluxes in two drained Northern peatlands

<p>Peatlands store large amounts of organic carbon, which is subject to microbial decomposition and mineralization to either CO<sub>2</sub> or CH<sub>4</sub>.  Drained peatlands are characterized by large horizontal variability in soil water contents and saturation, with dryer parts closer to the drainage ditches. The greenhouse gas (GHG) production in these systems is expected to be sensitive to temperature, substrate chemistry, oxygen concentration thus on soil water contents. Methane production should take place in the wetter parts, while respiration should dominate in drier parts. The seasonality of weather conditions modulates the spatial variability. In this complex situation, we are interested in how the seasonal weather variability triggers the microbial processes in the different micro-topographical situations and how this affects the overall GHG budgets of such sites.</p><p>We investigate two neighboring, drained ombrotrophic bogs in Norway close to Trysil, Innlandet, 61.1N- 12.25E, 640 m a. s. l.. One site (South) on an upper slope is about 45 m higher than the other site (North) in a saddle like flattening.  We use an automated chamber method to examine the seasonality of GHG production at microsites that cover some contrasting local situations with in the large range of small scale spatial heterogeneity. With eddy covariance CO<sub>2</sub> and CH<sub>4</sub> flux measurements, we integrate over a larger spatial scale, with, however, shifting footprints depending on weather conditions and wind direction. We present a comparative  analysis of 1.5 years continuous measurements, where we examine shifting spatial patterns of GHG production at different scales and relate them to soil conditions.</p><p>While the CO<sub>2</sub> fluxes compared very well between the two investigated sites, the CH<sub>4</sub> fluxes in the lower and wetter of the two sites (North) was higher and their spatial variability was lower than in the South site. Only in the South site, the CH<sub>4</sub> fluxes correlated with the coverage of well drained versus less well drained areas. We will present results on how the spatial variability changed with the seasonality of soil temperatures and the water table.</p><p>The automated chambers (five chambers within each footprint of the eddy flux towers) showed higher spatial variability for CH<sub>4</sub> fluxes than for CO<sub>2</sub> with higher CH<sub>4</sub> emissions in the wetter plots furthest away from ditches, i.e. CH<sub>4</sub> fluxes correlate well to ground water depth at both sites. N<sub>2</sub>O emissions were observed in short events during the early summer season. Overall, there was a good alignment of fluxes measured with eddy flux and chamber technologies.</p><p>Information on factors that constrain the spatio-temporal variability are important for estimating areal GHG budgets and for predicting possible effects of peatland management, such as draining or re-wetting on the climate effects from these ecosystems.  From the results, we expect higher effects of peatland restoration on GHG budgets in the South site.</p>

Inferring ecosystem-level rates of gross primary productivity, respiration, and evapotranspiration with automatic light-dark measurement chambers

<p>In experimental ecosystem ecology, plot sizes are most often too small to apply eddy flux techniques and estimation of ecosystem gas exchange rates relies on various chamber measurement technologies. Furthermore, drained areas often results in increased growth of trees which complicates application of eddy flux measurements on small plots.</p><p>We combined ECO<sub>2</sub>FluX ecosystem-level automatic chambers (prenart.dk) with an LI-8100/LI-8150 multiplexer systems (licor.com) in a range of Danish and Norwegian ecosystems experiments spanning agriculture, grassland/heathlands and peatland ecosystems. The automatic closed, none-steady state chambers each cover an area of 3,117 cm<sup>2</sup> (63 cm diameter), are 80 cm tall (volume: 250L), and are capable of switching automatically between transparent and darkened mode, enabling separation of light-sensitive and light-indifferent processes in the ecosystems covered. For CO<sub>2</sub> fluxes, net exchange (NEE) was estimated as the flux in transparent mode, ecosystem respiration (R<sub>E</sub>) in darkened mode, while Gross Ecosystem Productivity (GPP) was estimated as NEE – R<sub>E</sub>.</p><p>Chambers were set up to measure gas concentrations every second using enclosure times of 4-5 minutes, first in light mode and 10-30 minutes later in dark mode, with 3-48 repetitions per day. The longest time series spans 5 years of measurements and contain >60,000 point measurements.</p><p>In this presentation, we will present an analysis of the ability of the light-dark chamber data to infer ecosystem-level rates of gross primary productivity, respiration, net CO<sub>2</sub> exchange, and evapotranspiration. In the two Norwegian peatland sites, flux measurements may be compared directly with eddy flux measurements. We also compare the rates of the direct estimates of GPP from the light-dark chamber measurements to estimates inferred from using the light (NEE) measurements only followed by applying methodologies normally used for eddy flux measurements. This comparison may help constrain potential biases in both the closed chamber and eddy flux techniques. Finally, we investigate the ability of using such closed chambers to estimate ecosystem evapotranspiration rates at the plot scale. Such application may be useful for estimating the effects on evapotranspiration in field-scale experiments manipulating the ecosystem water balance either directly or indirectly.</p>

A dataset of microclimate and radiation and energy fluxes from the Lake Taihu eddy flux network

Eddy covariance data are widely used for the investigation of surface–air interactions. Although numerous datasets exist in public depositories for land ecosystems, few research groups have released eddy covariance data collected over lakes. In this paper, we describe a dataset from the Lake Taihu eddy flux network, a network consisting of seven lake sites and one land site. Lake Taihu is the third-largest freshwater lake (area of 2400 km2) in China, under the influence of subtropical climate. The dataset spans the period from June 2010 to December 2018. Data variables are saved as half-hourly averages and include micrometeorology (air temperature, humidity, wind speed, wind direction, rainfall, and water or soil temperature profile), the four components of surface radiation balance, friction velocity, and sensible and latent heat fluxes. Except for rainfall and wind direction, all other variables are gap-filled, with each data point marked by a quality flag. Several areas of research can potentially benefit from the publication of this dataset, including evaluation of mesoscale weather forecast models, development of lake–air flux parameterizations, investigation of climatic controls on lake evaporation, validation of remote-sensing surface data products and global synthesis on lake–air interactions. The dataset is publicly available at https://yncenter.sites.yale.edu/data-access (last access: 24 October 2020) and from the Harvard Dataverse (https://doi.org/10.7910/DVN/HEWCWM; Zhang et al., 2020).

A Geometric Perspective on the Modulation of Potential Energy Release by a Lateral Potential Vorticity Gradient

The release of available potential energy by growing baroclinic instability requires the slope of the eddy fluxes to be shallower than that of mean density surfaces, where the amount of energy released depends on both the flux angle and the distance of fluid parcel excursions against the background density gradient. The presence of a lateral potential vorticity (PV) gradient is known to affect the growth rate and energy release by baroclinic instability, but often makes the mathematics of formal linear stability analysis intractable. Here the effects of a lateral PV gradient on baroclinic growth are examined by considering its effects on the slope of the eddy fluxes. It is shown that the PV gradient systematically shifts the unstable modes toward higher wavenumbers and creates a cutoff to the instability at large scales, both of which steepen the eddy flux angle and limit the amount of energy released. This effect may contribute to the severe inhibition of baroclinic turbulence in systems dominated by barotropic jets, making them less likely to transition to turbulence-dominated flow regimes.

A dataset of microclimate and radiation and energy fluxes from the Lake Taihu Eddy Flux Network

Eddy covariance data are widely used for the investigation of surface-air interactions. Although numerical datasets exist in public depositories for upland ecosystems, few research groups have released eddy covariance data collected over lakes. In this paper, we describe a dataset from the Lake Taihu Eddy Flux Network, a network consisting of seven lake sites and one land site. Lake Taihu is the third largest freshwater lake (area 2,400 km2) in China, under the influence of subtropical climate. The dataset spans the period from June 2010 to December 2018. Data variables are recorded at half-hourly intervals and include micrometeorology (air temperature, humidity, wind speed, wind direction, rainfall, and water/soil temperature profile), the four components of surface radiation balance, friction velocity, and sensible and latent heat fluxes. Except for rainfall and wind direction, all other variables are gap-filled, with each datapoint marked by a quality flag. Several areas of research can potentially benefit from the publication of this dataset, including evaluation of mesoscale weather forecast models, development of lake-air flux parameterizations, investigation of climatic controls on lake evaporation, validation of remote sensing surface data products, and global synthesis on lake-air interactions. The dataset is publicly available at https://yncenter.sites.yale.edu/data-access and from Harvard Dataverse (doi: 10.7910/DVN/HEWCWM)

Quantifying contributions of uncertainties in physical parameterization schemes and model parameters to overall errors in Noah-MP land modeling using observations from eddy flux sites

<p>Quantifying contributions of errors in model structure and model parameters to biases in a land surface model (LSM) is critical for model improvement, but has not been done systematically for many global land surface models. This paper investigates the uncertainties in the Noah with multiparameterization (Noah-MP) LSM with dynamic vegetation by examining the interactions between imperfect parameterization schemes (PSs) and improper parameter values (PVs). A number of Noah-MP physical ensemble simulations were conducted at 92 eddy flux sites to quantitatively assess the impacts of the PS uncertainties on model performance, and then the key parameters in the two combinations of schemes with significant differences were calibrated. The results show that five subprocesses—the surface exchange coefficient (SFC), soil moisture threshold, radiation transfer (RAD), runoff and groundwater, and surface resistance to evaporation—have the most significant influence on the performances of simulated sensible heat flux, latent heat flux, net absorbed radiation and gross primary productivity in the Noah-MP LSM with dynamic vegetation, and that the interaction between SFC and RAD contributed up to 80% of the variation in the model performance at some sites. It is also shown that tuning the PSs and optimizing the PVs should be jointly applied to reduce the errors in the Noah-MP LSM, although compared to tuning PSs, parameter optimization happens to make less robust model improvement. Finally, this study emphasizes that reducing the significant uncertainties in soil parameters and exploring the errors caused by missing physical features are crucial to improving LSMs with dynamic vegetation.</p>