A few studies on ozone deposition over lake water are available and so far only one using the eddy covariance technique (Wesely et al., 1981, https://doi.org/10.1007/BF00122295). A 23‐day field ...campaign was held in August‐September 2012 at the Lake Kuivajärvi in Hyytiälä, Finland. The results showed a mean flux of −30 ± 1 ng m−2 s−1 and deposition velocity of 0.86 ± 0.05 mm s−1. Deposition velocity showed a weak diurnal cycle over the lake with elevated values during the nighttime. The daytime and nighttime portions of the data set differed statistically. Analysis showed that waterside convective mixing enhanced deposition and such conditions pre‐dominantly occurred during nighttime. We compared the measured deposition velocities with the dry deposition model of air‐sea exchange, adjusted for the chemical sinks relevant for the lake. We suggest that the buoyant mixing and unaccounted chemistry can be responsible for the difference between the model results and observations.
Plain Language Summary
Ozone deposition was studied over lake in Southern Finland. Deposition velocity showed elevated values during the nighttime. Higher ozone deposition at night was related to enhanced convective mixing in uppermost water layers.
Key Points
Ozone deposition over the lake is enhanced by waterside buoyancy velocity
Wind speed and friction velocity had minor or no impact on ozone deposition, instead waterside convective mixing enhanced deposition
In late summer, over diurnal course higher deposition velocities occurred at night
The loss of ozone to terrestrial and aquatic systems, known as dry deposition, is a highly uncertain process governed by turbulent transport, interfacial chemistry, and plant physiology. We ...demonstrate the value of using Deep Neural Networks (DNN) in predicting ozone dry deposition velocities. We find that a feedforward DNN trained on observations from a coniferous forest site (Hyytiälä, Finland) can predict hourly ozone dry deposition velocities at a mixed forest site (Harvard Forest, Massachusetts) more accurately than modern theoretical models, with a reduction in the normalized mean bias (0.05 versus ~0.1). The same DNN model, when driven by assimilated meteorology at 2° × 2.5° spatial resolution, outperforms the Wesely scheme as implemented in the GEOS‐Chem model. With more available training data from other climate and ecological zones, this methodology could yield a generalizable DNN suitable for global models.
Plain Language Summary
Ozone in the lower atmosphere is a toxic pollutant and greenhouse gas. In this work, we use a machine learning technique known as deep learning, to simulate the loss of ozone to Earth's surface. We show that our deep learning simulation of this loss process outperforms existing traditional models and demonstrate the opportunity for using machine learning to improve our understanding of the chemical composition of the atmosphere.
Key Points
We develop a deep learning parameterization for ozone dry deposition velocities
The deep learning parameterization outperforms existing physical models
Purpose
Aerenchymous plants are an important control for methane efflux from peatlands to the atmosphere, providing a bypass from the anoxic peat and avoiding oxidation in the oxic peat. We aimed to ...quantify the drivers of aerenchymous peatland species methane transport and the importance of this process for ecosystem-scale methane efflux.
Methods
We measured seasonal and interspecies variation in methane transport rate per gram of plant dry mass at a boreal fen and bog, which were upscaled to ecosystem-scale plant methane transport.
Results
Methane transport rate was better explained by plant species, leaf greenness and area than by environmental variables. Leaves appeared to transport methane even after senescence. Contrary to our expectations, both methane transport rate and the proportion of plant transport were lower in the fen (with greater sedge cover) than in the bog site. At the fen and bog, average methane transport rate was 0.7 and 1.8 mg g
−1
d
−1
, and the proportion of seasonally variable plant transport was 7–41% and 6–90%, respectively. Species-specific differences in methane transport rate were observed at the ecosystem-scale:
Scheuchzeria palustris,
which accounted for 16% of the aerenchymous leaf area in the fen and displayed the greatest methane transport rate, was responsible for 45% of the ecosystem-scale plant transport.
Conclusion
Our study showed that plant species influence the magnitude of ecosystem-scale methane emissions through their properties of methane transport. The identification and quantification of these properties could be the pivotal next step in predicting plant methane transport in peatlands.
We analysed the effect of the 2018 European drought on greenhouse gas (GHG) exchange of five North European mire ecosystems. The low precipitation and high summer temperatures in Fennoscandia led to ...a lowered water table in the majority of these mires. This lowered both carbon dioxide (CO
) uptake and methane (CH
) emission during 2018, turning three out of the five mires from CO
sinks to sources. The calculated radiative forcing showed that the drought-induced changes in GHG fluxes first resulted in a cooling effect lasting 15-50 years, due to the lowered CH
emission, which was followed by warming due to the lower CO
uptake. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.
Inland waters, such as lakes, reservoirs and rivers, are important sources of climate forcing trace gases. A key parameter that regulates the gas exchange between water and the atmosphere is the gas ...transfer velocity, which itself is controlled by near‐surface turbulence in the water. While in lakes and reservoirs, near‐surface turbulence is mainly driven by atmospheric forcing, in shallow rivers and streams it is generated by bottom friction of gravity‐forced flow. Large rivers represent a transition between these two cases. Near‐surface turbulence has rarely been measured in rivers and the drivers of turbulence have not been quantified. We analyzed continuous measurements of flow velocity and quantified turbulence as the rate of dissipation of turbulent kinetic energy over the ice‐free season in a large regulated river in Northern Finland. Measured dissipation rates agreed with predictions from bulk parameters, including mean flow velocity, wind speed, surface heat flux, and with a one‐dimensional numerical turbulence model. Values ranged from ∼10−10m2s−3 to 10−5m2s−3. Atmospheric forcing or gravity was the dominant driver of near‐surface turbulence for similar fraction of the time. Large variability in near‐surface dissipation rate occurred at diel time scales, when the flow velocity was strongly affected by downstream dam operation. By combining scaling relations for boundary‐layer turbulence at the river bed and at the air‐water interface, we derived a simple model for estimating the relative contributions of wind speed and bottom friction of river flow as a function of depth.
Plain Language Summary
Inland water bodies such as lakes, reservoirs and rivers are an important source of climate forcing trace gases to the atmosphere. Gas exchange between water and the atmosphere is regulated by the gas transfer velocity and the concentration difference between the water surface and the atmosphere. The gas transfer velocity depends on near‐surface turbulence, but robust formulations have not been developed for river systems. Their surface area is sufficiently large for meteorological forcing to cause turbulence, as in lakes and reservoirs, but turbulence generated from bed and internal friction of gravity‐driven flows is also expected to contribute. Here we quantify near‐surface turbulence using data from continuous air and water side measurements conducted over the ice‐free season in a large subarctic regulated river in Finland. We find that turbulence, quantified as the dissipation rate of turbulent kinetic energy, is well described using equations for predicting turbulence from meteorological data for sufficiently high wind speeds whereas the contribution from bottom shear dominated at higher flow velocities. A one‐dimensional river model successfully captured these processes. We provide a fundamental model for estimating the relative contributions of atmospheric forcing and bottom friction as a function of depth.
Key Points
Wind and river flow make comparable contributions to near‐surface turbulence in a regulated river
Dissipation rates predicted from wind speed and flow velocity are in good agreement with observations
Diel variability in dissipation rates occurs in response to flow regulation and atmospheric forcing
Droughts can have an impact on forest functioning and production, and even lead to tree mortality. However, drought is an elusive phenomenon that is difficult to quantify and define universally. In ...this study, we assessed the performance of a set of indicators that have been used to describe drought conditions in the summer months (June, July, August) over a 30-year period (1981–2010) in Finland. Those indicators include the Standardized Precipitation Index (SPI), the Standardized Precipitation–Evapotranspiration Index (SPEI), the Soil Moisture Index (SMI), and the Soil Moisture Anomaly (SMA). Herein, regional soil moisture was produced by the land surface model JSBACH of the Max Planck Institute for Meteorology Earth System Model (MPI-ESM). Results show that the buffering effect of soil moisture and the associated soil moisture memory can impact on the onset and duration of drought as indicated by the SMI and SMA, while the SPI and SPEI are directly controlled by meteorological conditions. In particular, we investigated whether the SMI, SMA and SPEI are able to indicate the Extreme Drought affecting Forest health (EDF), which we defined according to the extreme drought that caused severe forest damages in Finland in 2006. The EDF thresholds for the aforementioned indicators are suggested, based on the reported statistics of forest damages in Finland in 2006. SMI was found to be the best indicator in capturing the spatial extent of forest damage induced by the extreme drought in 2006. In addition, through the application of the EDF thresholds over the summer months of the 30-year study period, the SPEI and SMA tended to show more frequent EDF events and a higher fraction of influenced area than SMI. This is because the SPEI and SMA are standardized indicators that show the degree of anomalies from statistical means over the aggregation period of climate conditions and soil moisture, respectively. However, in boreal forests in Finland, the high initial soil moisture or existence of peat often prevent the EDFs indicated by the SPEI and SMA to produce very low soil moisture that could be indicated as EDFs by the SMI. Therefore, we consider SMI is more appropriate for indicating EDFs in boreal forests. The selected EDF thresholds for those indicators could be calibrated when there are more forest health observation data available. Furthermore, in the context of future climate scenarios, assessments of EDF risks in northern areas should, in addition to climate data, rely on a land surface model capable of reliable prediction of soil moisture.
The objective of this review is to examine and evaluate recent findings on cognitive functioning (in particular imagery processes) in individuals with congenital visual impairments, including total ...blindness, low-vision and monocular vision. As one might expect, the performance of blind individuals in many behaviours and tasks requiring imagery can be inferior to that of sighted subjects; however, surprisingly often this is not the case. Interestingly, there is evidence that the blind often employ different cognitive mechanisms than sighted subjects, suggesting that compensatory mechanisms can overcome the limitations of sight loss. Taken together, these studies suggest that the nature of perceptual input on which we commonly rely strongly affects the organization of our mental processes. We also review recent neuroimaging studies on the neural correlates of sensory perception and mental imagery in visually impaired individuals that have cast light on the plastic functional reorganization mechanisms associated with visual deprivation.
•The applicability of a forest flux ecosystem model to the Boreal region was tested.•Eddy-covariance measurements from 10 sites were used to evaluate the model.•We compared the performances of ...multi-site (M-S) vs site-specific (S-S) calibrations.•M-S showed robust results and can be used for regional applications.•Long and carefully collected flux dataset leads to better model performances.
Simple models are less input demanding and their calibration involves a lower number of parameters, however their general applicability to vast areas must be tested. We analysed if a simple ecosystem model (PRELES) can be applied to estimate carbon and water fluxes of Boreal forests at regional scale.
Multi-site (M-S) and site-specific (S-S) calibrations were compared using evapotranspiration (ET) and gross primary production (GPP) measurements from 10 sites. The performances of M-S were similar to S-Ss except for a site with agricultural history. Although PRELES predicted GPP better than ET, we concluded that the model can be reliably used at regional scale to simulate carbon and water fluxes of Boreal forests.
We further found that, in the calibration, the use of a long and carefully collected flux dataset from one site that covers a wide range of climate variability leads to better model performance in other sites as well.
Dry deposition could partially explain the observed response in ambient ozone to extreme hot and dry episodes. We examine the response of ozone deposition to heat and dry anomalies using three ...long‐term co‐located ecosystem‐scale carbon dioxide, water vapor and ozone flux measurement records. We find that, as expected, canopy stomatal conductance generally decreases during days with dry air or soil. However, during hot days, concurrent increases in non‐stomatal conductance are inferred at all three sites, which may be related to several temperature‐sensitive processes not represented in the current generation of big‐leaf models. This may offset the reduction in stomatal conductance, leading to smaller net reduction, or even net increase, in total deposition velocity. We find the response of deposition velocity to soil dryness may be related to its impact on photosynthetic activity, though considerable variability exists. Our findings emphasize the need for better understanding and representation of non‐stomatal ozone deposition.
Plain Language Summary
Ozone is an important air pollutant that can threaten both human and plant health. Removal of ozone from the atmosphere may be reduced during extremely hot or dry events due to how plants respond to such environmental conditions (governed by stomatal or non‐stomatal processes separately). Using long‐term observations at three different sites, we find that non‐stomatal uptake generally increases on hot days, which can offset a reduction in stomatal uptake that is expected under the same conditions. The response to soil dryness is more complicated, but potentially related to responses in photosynthetic activity. Current models of on how ozone deposition affects surface ozone concentrations during hot and dry episodes are inaccurate because of their inability to represent non‐stomatal responses.
Key Points
Responses of total ozone deposition to heat and dry anomalies vary considerably from site to site
Non‐stomatal deposition increases significantly during hot days in all three sites considered
Current big‐leaf parameterizations largely fail to capture the response mainly because of non‐stomatal deposition
Performances of four methane gas analyzers suitable for eddy covariance measurements are assessed. The assessment and comparison was performed by analyzing eddy covariance data obtained during summer ...2010 (1 April to 26 October) at a pristine fen, Siikaneva, Southern Finland. High methane fluxes with pronounced seasonality have been measured at this fen. The four participating methane gas analyzers are commercially available closed-path units TGA-100A (Campbell Scientific Inc., USA), RMT-200 (Los Gatos Research, USA), G1301-f (Picarro Inc., USA) and an early prototype open-path unit Prototype-7700 (LI-COR Biosciences, USA). The RMT-200 functioned most reliably throughout the measurement campaign, during low and high flux periods. Methane fluxes from RMT-200 and G1301-f had the smallest random errors and the fluxes agree remarkably well throughout the measurement campaign. Cospectra and power spectra calculated from RMT-200 and G1301-f data agree well with corresponding temperature spectra during a high flux period. None of the gas analyzers showed statistically significant diurnal variation for methane flux. Prototype-7700 functioned only for a short period of time, over one month, in the beginning of the measurement campaign during low flux period, and thus, its overall accuracy and season-long performance were not assessed. The open-path gas analyzer is a practical choice for measurement sites in remote locations due to its low power demand, whereas for G1301-f methane measurements interference from water vapor is straightforward to correct since the instrument measures both gases simultaneously. In any case, if only the performance in this intercomparison is considered, RMT-200 performed the best and is the recommended choice if a new fast response methane gas analyzer is needed.
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