2020
|
Randazzo, Nina A; Michalak, Anna M; Desai, Ankur R: Synoptic Meteorology Explains Temperate Forest Carbon Uptake. In: Journal of Geophysical Research: Biogeosciences, vol. 125, no. 2, pp. e2019JG005476, 2020, (e2019JG005476 2019JG005476). @article{https://doi.org/10.1029/2019JG005476,
title = {Synoptic Meteorology Explains Temperate Forest Carbon Uptake},
author = {Nina A Randazzo and Anna M Michalak and Ankur R Desai},
url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2019JG005476},
doi = {https://doi.org/10.1029/2019JG005476},
year = {2020},
date = {2020-01-16},
journal = {Journal of Geophysical Research: Biogeosciences},
volume = {125},
number = {2},
pages = {e2019JG005476},
abstract = {Abstract While substantial attention has been paid to the effects of both global climate oscillations and local meteorological conditions on the interannual variability of ecosystem carbon exchange, the relationship between the interannual variability of synoptic meteorology and ecosystem carbon exchange has not been well studied. Here we use a clustering algorithm to identify a summertime cyclonic precipitation system northwest of the Great Lakes to determine (a) the association at a daily scale between the occurrence of this system and the local meteorology and net ecosystem exchange at three Great Lakes region forested eddy covariance sites and (b) the association between the seasonal prevalence of this system and the summertime net ecosystem exchange of these sites. We find that temperature, in addition to precipitation and cloud cover, is an important explanatory factor for the suppression of net ecosystem productivity that occurs during these cyclonic events in this region. In addition, the prevalence of this cyclonic system can explain a significant proportion of the interannual variability in summertime forest ecosystem exchange in this region. This explanatory power is not due to a simple accumulation of low-productivity days that cooccur with this meteorological event, but rather a broader association between the frequency of these events and several aspects of prevailing seasonal conditions. This work demonstrates the usefulness of conceptualizing meteorology in terms of synoptic systems for explaining the interannual variability of regional carbon fluxes.},
note = {e2019JG005476 2019JG005476},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Abstract While substantial attention has been paid to the effects of both global climate oscillations and local meteorological conditions on the interannual variability of ecosystem carbon exchange, the relationship between the interannual variability of synoptic meteorology and ecosystem carbon exchange has not been well studied. Here we use a clustering algorithm to identify a summertime cyclonic precipitation system northwest of the Great Lakes to determine (a) the association at a daily scale between the occurrence of this system and the local meteorology and net ecosystem exchange at three Great Lakes region forested eddy covariance sites and (b) the association between the seasonal prevalence of this system and the summertime net ecosystem exchange of these sites. We find that temperature, in addition to precipitation and cloud cover, is an important explanatory factor for the suppression of net ecosystem productivity that occurs during these cyclonic events in this region. In addition, the prevalence of this cyclonic system can explain a significant proportion of the interannual variability in summertime forest ecosystem exchange in this region. This explanatory power is not due to a simple accumulation of low-productivity days that cooccur with this meteorological event, but rather a broader association between the frequency of these events and several aspects of prevailing seasonal conditions. This work demonstrates the usefulness of conceptualizing meteorology in terms of synoptic systems for explaining the interannual variability of regional carbon fluxes. |
Barnes, Ben Davis; Husson, Jon M; Peters, Shanan E: Authigenic carbonate burial in the Late Devonian–Early Mississippian Bakken Formation (Williston Basin, USA). In: Sedimentology, vol. 67, no. 4, pp. 2065-2094, 2020. @article{https://doi.org/10.1111/sed.12695,
title = {Authigenic carbonate burial in the Late Devonian–Early Mississippian Bakken Formation (Williston Basin, USA)},
author = {Ben Davis Barnes and Jon M Husson and Shanan E Peters},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/sed.12695},
doi = {https://doi.org/10.1111/sed.12695},
year = {2020},
date = {2020-01-01},
journal = {Sedimentology},
volume = {67},
number = {4},
pages = {2065-2094},
abstract = {Abstract Late Devonian (Famennian) marine successions globally are typified by organic-rich black shales deposited in anoxic and euxinic waters and the cessation of shelf carbonate sedimentation. This global ‘carbonate crisis’, known as the Hangenberg Event, coincides with a major extinction of reef-building metazoans and perturbations to the global carbon cycle, evidenced by positive carbon-isotope excursions of up to 4‰. It has been suggested that authigenic carbonate, formed as cements in sedimentary pore spaces during early burial diagenesis, is a significant mass fraction of the total global carbon burial flux, particularly during periods of low oxygen concentration. Because some authigenic carbonate could have originated from remineralization of organic carbon in sediments, it is possible for this reservoir to be isotopically depleted and thereby drive changes in the carbon isotopic composition of seawater. This study presents bulk isotopic and elemental analyses from fine-grained siliciclastics of the Late Devonian–Early Mississippian Bakken Formation (Williston Basin, USA) to assess the volume and isotopic composition of carbonates in these sediments. Carbonate in the Bakken black shales occurs primarily as microscopic disseminated dolomite rhombs and calcite cements that, together, comprise a significant mass-fraction (ca 9%). The elemental composition of the shales is indicative of a dynamic anoxic to sulphidic palaeoenvironment, likely supported by a fluctuating chemocline. Despite forming in an environment favourable to remineralization of organic matter and the precipitation of isotopically depleted authigenic carbonates, the majority of carbon isotope measurements of disseminated carbonate fall between −3‰ and +3‰, with systematically more depleted carbonates in the deeper-water portions of the basin. Thus, although there is evidence for a significant total mass-fraction of carbonate with contribution from remineralized organic matter, Bakken authigenic carbonates suggest that Famennian black shales are unlikely to be sufficiently 13C-depleted relative to water column dissolved inorganic carbon to serve as a major lever on seawater isotopic composition.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Abstract Late Devonian (Famennian) marine successions globally are typified by organic-rich black shales deposited in anoxic and euxinic waters and the cessation of shelf carbonate sedimentation. This global ‘carbonate crisis’, known as the Hangenberg Event, coincides with a major extinction of reef-building metazoans and perturbations to the global carbon cycle, evidenced by positive carbon-isotope excursions of up to 4‰. It has been suggested that authigenic carbonate, formed as cements in sedimentary pore spaces during early burial diagenesis, is a significant mass fraction of the total global carbon burial flux, particularly during periods of low oxygen concentration. Because some authigenic carbonate could have originated from remineralization of organic carbon in sediments, it is possible for this reservoir to be isotopically depleted and thereby drive changes in the carbon isotopic composition of seawater. This study presents bulk isotopic and elemental analyses from fine-grained siliciclastics of the Late Devonian–Early Mississippian Bakken Formation (Williston Basin, USA) to assess the volume and isotopic composition of carbonates in these sediments. Carbonate in the Bakken black shales occurs primarily as microscopic disseminated dolomite rhombs and calcite cements that, together, comprise a significant mass-fraction (ca 9%). The elemental composition of the shales is indicative of a dynamic anoxic to sulphidic palaeoenvironment, likely supported by a fluctuating chemocline. Despite forming in an environment favourable to remineralization of organic matter and the precipitation of isotopically depleted authigenic carbonates, the majority of carbon isotope measurements of disseminated carbonate fall between −3‰ and +3‰, with systematically more depleted carbonates in the deeper-water portions of the basin. Thus, although there is evidence for a significant total mass-fraction of carbonate with contribution from remineralized organic matter, Bakken authigenic carbonates suggest that Famennian black shales are unlikely to be sufficiently 13C-depleted relative to water column dissolved inorganic carbon to serve as a major lever on seawater isotopic composition. |
Fastovich, David; Russell, James M; Jackson, Stephen T; Williams, John W: Deglacial temperature controls on no-analog community establishment in the Great Lakes Region. In: Quaternary Science Reviews, vol. 234, pp. 106245, 2020, ISSN: 0277-3791. @article{FASTOVICH2020106245,
title = {Deglacial temperature controls on no-analog community establishment in the Great Lakes Region},
author = {David Fastovich and James M Russell and Stephen T Jackson and John W Williams},
url = {https://www.sciencedirect.com/science/article/pii/S0277379119303713},
doi = {https://doi.org/10.1016/j.quascirev.2020.106245},
issn = {0277-3791},
year = {2020},
date = {2020-01-01},
journal = {Quaternary Science Reviews},
volume = {234},
pages = {106245},
abstract = {Understanding the drivers of vegetation dynamics and no-analog communities in eastern North America is hampered by a scarcity of independent temperature indicators. We present a new branched glycerol dialkyl glycerol tetraether (brGDGT) temperature record from Bonnet Lake, Ohio (18–8 ka) and report uncertainty estimates based on Bayesian linear regression and bootstrapping. We also reanalyze a previously published brGDGT record from Silver Lake, Ohio, using improved chromatographic methods. All pollen- and brGDGT-based temperature reconstructions showed qualitatively similar deglacial trends but varying magnitudes. Separating 5- and 6- methyl brGDGTs resulted in substantially lower estimates of deglacial temperature variations (6.4 °C) than inferred from earlier brGDGT methods and pollen (11.8 °C, 12.0 °C respectively). Similar trends among proxies suggest good fidelity of brGDGTs to temperature, despite calibration uncertainties. At both sites, the rise and decline of no-analog communities closely track brGDGT-inferred temperatures, with a lag of 0–150 years. The timing of temperature and ecological events varies between Bonnet and Silver Lakes, likely due to age model uncertainties. Climate sensitivity analyses indicate a linear sensitivity of vegetation composition to temperature variations, albeit noisy and significant only with a 500-year bin. The formation of no-analog plant communities in the upper Midwest is closely linked to late-glacial warming, but other factors, such as temperature seasonality or end-Pleistocene megafaunal extinctions, remain viable.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Understanding the drivers of vegetation dynamics and no-analog communities in eastern North America is hampered by a scarcity of independent temperature indicators. We present a new branched glycerol dialkyl glycerol tetraether (brGDGT) temperature record from Bonnet Lake, Ohio (18–8 ka) and report uncertainty estimates based on Bayesian linear regression and bootstrapping. We also reanalyze a previously published brGDGT record from Silver Lake, Ohio, using improved chromatographic methods. All pollen- and brGDGT-based temperature reconstructions showed qualitatively similar deglacial trends but varying magnitudes. Separating 5- and 6- methyl brGDGTs resulted in substantially lower estimates of deglacial temperature variations (6.4 °C) than inferred from earlier brGDGT methods and pollen (11.8 °C, 12.0 °C respectively). Similar trends among proxies suggest good fidelity of brGDGTs to temperature, despite calibration uncertainties. At both sites, the rise and decline of no-analog communities closely track brGDGT-inferred temperatures, with a lag of 0–150 years. The timing of temperature and ecological events varies between Bonnet and Silver Lakes, likely due to age model uncertainties. Climate sensitivity analyses indicate a linear sensitivity of vegetation composition to temperature variations, albeit noisy and significant only with a 500-year bin. The formation of no-analog plant communities in the upper Midwest is closely linked to late-glacial warming, but other factors, such as temperature seasonality or end-Pleistocene megafaunal extinctions, remain viable. |
Ruddiman, W F; He, F; Vavrus, S J; Kutzbach, J E: The early anthropogenic hypothesis: A review. In: Quaternary Science Reviews, vol. 240, pp. 106386, 2020, ISSN: 0277-3791. @article{RUDDIMAN2020106386,
title = {The early anthropogenic hypothesis: A review},
author = {W F Ruddiman and F He and S J Vavrus and J E Kutzbach},
url = {https://www.sciencedirect.com/science/article/pii/S0277379120303486},
doi = {https://doi.org/10.1016/j.quascirev.2020.106386},
issn = {0277-3791},
year = {2020},
date = {2020-01-01},
journal = {Quaternary Science Reviews},
volume = {240},
pages = {106386},
abstract = {The ‘early anthropogenic hypothesis’ (EAH), published in 2003, proposed that early agricultural humans transformed planet Earth by adding CO2 to the atmosphere by deforestation after 7000 years ago and by adding CH4 to the atmosphere by wet-rice farming and livestock tending after 5000 years ago. Later work led to the insight that the resulting warming of the atmosphere and the ocean would have contributed additional CO2 feedback by reducing CO2 solubility in the global ocean and by boosting ventilation from the Antarctic Ocean surface due to suppressed Antarctic sea-ice extent. This paper summarizes new findings from multiple scientific disciplines that document how the steadily spreading human influence transformed their environment after 7000 years ago. We blend this new evidence into a revised version of the EAH, and we also evaluate proposed alternatives to the anthropogenic explanation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The ‘early anthropogenic hypothesis’ (EAH), published in 2003, proposed that early agricultural humans transformed planet Earth by adding CO2 to the atmosphere by deforestation after 7000 years ago and by adding CH4 to the atmosphere by wet-rice farming and livestock tending after 5000 years ago. Later work led to the insight that the resulting warming of the atmosphere and the ocean would have contributed additional CO2 feedback by reducing CO2 solubility in the global ocean and by boosting ventilation from the Antarctic Ocean surface due to suppressed Antarctic sea-ice extent. This paper summarizes new findings from multiple scientific disciplines that document how the steadily spreading human influence transformed their environment after 7000 years ago. We blend this new evidence into a revised version of the EAH, and we also evaluate proposed alternatives to the anthropogenic explanation. |
Fitzpatrick, Megan J; Porter, Warren P; Pauli, Jonathan N; Kearney, Michael R; Notaro, Michael; Zuckerberg, Benjamin: Future winters present a complex energetic landscape of decreased costs and reduced risk for a freeze-tolerant amphibian, the Wood Frog (Lithobates sylvaticus). In: Global Change Biology, vol. 26, no. 11, pp. 6350-6362, 2020. @article{https://doi.org/10.1111/gcb.15321,
title = {Future winters present a complex energetic landscape of decreased costs and reduced risk for a freeze-tolerant amphibian, the Wood Frog (Lithobates sylvaticus)},
author = {Megan J Fitzpatrick and Warren P Porter and Jonathan N Pauli and Michael R Kearney and Michael Notaro and Benjamin Zuckerberg},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/gcb.15321},
doi = {https://doi.org/10.1111/gcb.15321},
year = {2020},
date = {2020-01-01},
journal = {Global Change Biology},
volume = {26},
number = {11},
pages = {6350-6362},
abstract = {Abstract Winter climate warming is rapidly leading to changes in snow depth and soil temperatures across mid- and high-latitude ecosystems, with important implications for survival and distribution of species that overwinter beneath the snow. Amphibians are a particularly vulnerable group to winter climate change because of the tight coupling between their body temperature and metabolic rate. Here, we used a mechanistic microclimate model coupled to an animal biophysics model to predict the spatially explicit effects of future climate change on the wintering energetics of a freeze-tolerant amphibian, the Wood Frog (Lithobates sylvaticus), across its distributional range in the eastern United States. Our below-the-snow microclimate simulations were driven by dynamically downscaled climate projections from a regional climate model coupled to a one-dimensional model of the Laurentian Great Lakes. We found that warming soil temperatures and decreasing winter length have opposing effects on Wood Frog winter energy requirements, leading to geographically heterogeneous implications for Wood Frogs. While energy expenditures and peak body ice content were predicted to decline in Wood Frogs across most of our study region, we identified an area of heightened energetic risk in the northwestern part of the Great Lakes region where energy requirements were predicted to increase. Because Wood Frogs rely on body stores acquired in fall to fuel winter survival and spring breeding, increased winter energy requirements have the potential to impact local survival and reproduction. Given the geographically variable and intertwined drivers of future under-snow conditions (e.g., declining snow depths, rising air temperatures, shortening winters), spatially explicit assessments of species energetics and risk will be important to understanding the vulnerability of subnivium-adapted species.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Abstract Winter climate warming is rapidly leading to changes in snow depth and soil temperatures across mid- and high-latitude ecosystems, with important implications for survival and distribution of species that overwinter beneath the snow. Amphibians are a particularly vulnerable group to winter climate change because of the tight coupling between their body temperature and metabolic rate. Here, we used a mechanistic microclimate model coupled to an animal biophysics model to predict the spatially explicit effects of future climate change on the wintering energetics of a freeze-tolerant amphibian, the Wood Frog (Lithobates sylvaticus), across its distributional range in the eastern United States. Our below-the-snow microclimate simulations were driven by dynamically downscaled climate projections from a regional climate model coupled to a one-dimensional model of the Laurentian Great Lakes. We found that warming soil temperatures and decreasing winter length have opposing effects on Wood Frog winter energy requirements, leading to geographically heterogeneous implications for Wood Frogs. While energy expenditures and peak body ice content were predicted to decline in Wood Frogs across most of our study region, we identified an area of heightened energetic risk in the northwestern part of the Great Lakes region where energy requirements were predicted to increase. Because Wood Frogs rely on body stores acquired in fall to fuel winter survival and spring breeding, increased winter energy requirements have the potential to impact local survival and reproduction. Given the geographically variable and intertwined drivers of future under-snow conditions (e.g., declining snow depths, rising air temperatures, shortening winters), spatially explicit assessments of species energetics and risk will be important to understanding the vulnerability of subnivium-adapted species. |
Delorit, Justin D; Block, Paul J: Cooperative water trade as a hedge against scarcity: Accounting for risk attitudes in the uptake of forecast-informed water option contracts. In: Journal of Hydrology, vol. 583, pp. 124626, 2020, ISSN: 0022-1694. @article{DELORIT2020124626,
title = {Cooperative water trade as a hedge against scarcity: Accounting for risk attitudes in the uptake of forecast-informed water option contracts},
author = {Justin D Delorit and Paul J Block},
url = {https://www.sciencedirect.com/science/article/pii/S002216942030086X},
doi = {https://doi.org/10.1016/j.jhydrol.2020.124626},
issn = {0022-1694},
year = {2020},
date = {2020-01-01},
journal = {Journal of Hydrology},
volume = {583},
pages = {124626},
abstract = {Season-ahead hydrologic forecasts hold the potential to inform water user decision making, provided forecast information offers value to targeted end-users, particularly in water-scarce regions. Yet, user willingness to trust forecast information is uncertain and often varied across similar user groups. Here, forecast uptake by agriculture users in semi-arid water rights managed basins is modelled to account for heterogeneous risk attitude and hydrologic variability. A season-ahead forecast of reservoir inflow is translated to water-trading rulesets through coupled reservoir allocation, i.e. per-water right allocation from the reservoir, crop-water, economic optimization, and demand derivation models. Theoretical growers, aligned in crop-type cooperatives, are modelled as potential exclusive water trading partners that, in years of scarcity may choose between forecast-informed water trading via option contracts, or one of two alternative water trade actions: persistence forecast-informed trading or no trading. Simulations across varied initial water rights endowment and farmer risk attitude allows for evaluation of expected investment of water rights in forecast-informed water trade. Results indicate farmer willingness to trust forecast information and subsequently invest rights option contracts trade is variable (28%–70%), and dependent on initial endowment of rights and alternative water trade action, manifested here as persistence-informed trade and no trade alternative. While variable, investment outcomes for probabilistic hydrologic simulations reveal long-term trade stability under nearly every forecast-informed water trading simulation, suggesting options contracts may be viable under a variety of water scarcity conditions. A key insight is that seasonal climate forecasts may prove to be quite valuable when translated through sectoral models, providing the tailored information to end users with diverse risk attitudes. This reinforces the potential in including forecasts in agricultural water resources decision support frameworks, as a hedge against water scarcity for farmers of varied earning potential.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Season-ahead hydrologic forecasts hold the potential to inform water user decision making, provided forecast information offers value to targeted end-users, particularly in water-scarce regions. Yet, user willingness to trust forecast information is uncertain and often varied across similar user groups. Here, forecast uptake by agriculture users in semi-arid water rights managed basins is modelled to account for heterogeneous risk attitude and hydrologic variability. A season-ahead forecast of reservoir inflow is translated to water-trading rulesets through coupled reservoir allocation, i.e. per-water right allocation from the reservoir, crop-water, economic optimization, and demand derivation models. Theoretical growers, aligned in crop-type cooperatives, are modelled as potential exclusive water trading partners that, in years of scarcity may choose between forecast-informed water trading via option contracts, or one of two alternative water trade actions: persistence forecast-informed trading or no trading. Simulations across varied initial water rights endowment and farmer risk attitude allows for evaluation of expected investment of water rights in forecast-informed water trade. Results indicate farmer willingness to trust forecast information and subsequently invest rights option contracts trade is variable (28%–70%), and dependent on initial endowment of rights and alternative water trade action, manifested here as persistence-informed trade and no trade alternative. While variable, investment outcomes for probabilistic hydrologic simulations reveal long-term trade stability under nearly every forecast-informed water trading simulation, suggesting options contracts may be viable under a variety of water scarcity conditions. A key insight is that seasonal climate forecasts may prove to be quite valuable when translated through sectoral models, providing the tailored information to end users with diverse risk attitudes. This reinforces the potential in including forecasts in agricultural water resources decision support frameworks, as a hedge against water scarcity for farmers of varied earning potential. |
2019
|
Xu, Ke; Pingintha-Durden, Natchaya; Luo, Hongyan; Durden, David; Sturtevant, Cove; Desai, Ankur R; Florian, Christopher; Metzger, Stefan: The eddy-covariance storage term in air: Consistent community resources improve flux measurement reliability. In: Agricultural and Forest Meteorology, vol. 279, pp. 107734, 2019, ISSN: 0168-1923. @article{XU2019107734,
title = {The eddy-covariance storage term in air: Consistent community resources improve flux measurement reliability},
author = {Ke Xu and Natchaya Pingintha-Durden and Hongyan Luo and David Durden and Cove Sturtevant and Ankur R Desai and Christopher Florian and Stefan Metzger},
url = {https://www.sciencedirect.com/science/article/pii/S0168192319303508},
doi = {https://doi.org/10.1016/j.agrformet.2019.107734},
issn = {0168-1923},
year = {2019},
date = {2019-12-15},
journal = {Agricultural and Forest Meteorology},
volume = {279},
pages = {107734},
abstract = {In the widely-used eddy-covariance (EC) technique, it is often assumed that the air storage term, i.e. the change of below-turbulence-sensor scalar abundance, is negligible or comprises a small part of net surface-atmosphere exchange (NSAE). Previous studies have demonstrated that this assumption is often violated where non-turbulent processes prevail, and thus it is important to measure and calculate air storage in flux measurements. However, the implementation of air storage measurement and calculation is not ubiquitous as EC standard turbulent flux. In most cases, air storage is not a standard data product or even neglected in EC flux tower measurements. In other cases, air storage term is calculated simply using only the measurements at the tower top. This gap between the ideal initiative and actual implementation motivates us to derive and release one of the first community resources to facilitate the consistent measurement and calculation of EC air storage across sites. These resources include (i) the standardized air storage term measurement setup design at National Ecological Observatory Network (NEON) sites; (ii) the development and public release of the eddy4R.stor open-source air storage R-package; (iii) the derivation and public release of storage term data products, measured and calculated consistently across 47 NEON sites; and (iv) exploration the scientific usefulness of these resources through example use cases, specifically the exploration of the bias of the air storage term when different measurement level intensity used and exploration of the air storage term pattern. We expect the consistent air storage measurement and calculation can better serve the overall purpose of the EC technique to provide more reliable measurement of NSAE for the community. This can further benefit the community accurate depiction of the sub-daily to diurnal cycle of surface fluxes in doing carbon cycle flux partitioning, land modeling, and studying ecosystem response to weather extremes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In the widely-used eddy-covariance (EC) technique, it is often assumed that the air storage term, i.e. the change of below-turbulence-sensor scalar abundance, is negligible or comprises a small part of net surface-atmosphere exchange (NSAE). Previous studies have demonstrated that this assumption is often violated where non-turbulent processes prevail, and thus it is important to measure and calculate air storage in flux measurements. However, the implementation of air storage measurement and calculation is not ubiquitous as EC standard turbulent flux. In most cases, air storage is not a standard data product or even neglected in EC flux tower measurements. In other cases, air storage term is calculated simply using only the measurements at the tower top. This gap between the ideal initiative and actual implementation motivates us to derive and release one of the first community resources to facilitate the consistent measurement and calculation of EC air storage across sites. These resources include (i) the standardized air storage term measurement setup design at National Ecological Observatory Network (NEON) sites; (ii) the development and public release of the eddy4R.stor open-source air storage R-package; (iii) the derivation and public release of storage term data products, measured and calculated consistently across 47 NEON sites; and (iv) exploration the scientific usefulness of these resources through example use cases, specifically the exploration of the bias of the air storage term when different measurement level intensity used and exploration of the air storage term pattern. We expect the consistent air storage measurement and calculation can better serve the overall purpose of the EC technique to provide more reliable measurement of NSAE for the community. This can further benefit the community accurate depiction of the sub-daily to diurnal cycle of surface fluxes in doing carbon cycle flux partitioning, land modeling, and studying ecosystem response to weather extremes. |
Knox, Sara H; Jackson, Robert B; Poulter, Benjamin; McNicol, Gavin; Fluet-Chouinard, Etienne; Zhang, Zhen; Hugelius, Gustaf; Bousquet, Philippe; Canadell, Josep G; Saunois, Marielle; Papale, Dario; Chu, Housen; Keenan, Trevor F; Baldocchi, Dennis; Torn, Margaret S; Mammarella, Ivan; Trotta, Carlo; Aurela, Mika; Bohrer, Gil; Campbell, David I; Cescatti, Alessandro; Chamberlain, Samuel; Chen, Jiquan; Chen, Weinan; Dengel, Sigrid; Desai, Ankur R; Euskirchen, Eugenie; Friborg, Thomas; Gasbarra, Daniele; Goded, Ignacio; Goeckede, Mathias; Heimann, Martin; Helbig, Manuel; Hirano, Takashi; Hollinger, David Y; Iwata, Hiroki; Kang, Minseok; Klatt, Janina; Krauss, Ken W; Kutzbach, Lars; Lohila, Annalea; Mitra, Bhaskar; Morin, Timothy H; Nilsson, Mats B; Niu, Shuli; Noormets, Asko; Oechel, Walter C; Peichl, Matthias; Peltola, Olli; Reba, Michele L; Richardson, Andrew D; Runkle, Benjamin R K; Ryu, Youngryel; Sachs, Torsten; Schäfer, Karina V R; Schmid, Hans Peter; Shurpali, Narasinha; Sonnentag, Oliver; Tang, Angela C I; Ueyama, Masahito; Vargas, Rodrigo; Vesala, Timo; Ward, Eric J; Windham-Myers, Lisamarie; Wohlfahrt, Georg; Zona, Donatella: FLUXNET-CH4 Synthesis Activity: Objectives, Observations, and Future Directions. In: Bulletin of the American Meteorological Society, vol. 100, no. 12, pp. 2607-2632, 2019. @article{Knox01Dec.2019,
title = {FLUXNET-CH4 Synthesis Activity: Objectives, Observations, and Future Directions},
author = {Sara H Knox and Robert B Jackson and Benjamin Poulter and Gavin McNicol and Etienne Fluet-Chouinard and Zhen Zhang and Gustaf Hugelius and Philippe Bousquet and Josep G Canadell and Marielle Saunois and Dario Papale and Housen Chu and Trevor F Keenan and Dennis Baldocchi and Margaret S Torn and Ivan Mammarella and Carlo Trotta and Mika Aurela and Gil Bohrer and David I Campbell and Alessandro Cescatti and Samuel Chamberlain and Jiquan Chen and Weinan Chen and Sigrid Dengel and Ankur R Desai and Eugenie Euskirchen and Thomas Friborg and Daniele Gasbarra and Ignacio Goded and Mathias Goeckede and Martin Heimann and Manuel Helbig and Takashi Hirano and David Y Hollinger and Hiroki Iwata and Minseok Kang and Janina Klatt and Ken W Krauss and Lars Kutzbach and Annalea Lohila and Bhaskar Mitra and Timothy H Morin and Mats B Nilsson and Shuli Niu and Asko Noormets and Walter C Oechel and Matthias Peichl and Olli Peltola and Michele L Reba and Andrew D Richardson and Benjamin R K Runkle and Youngryel Ryu and Torsten Sachs and Karina V R Schäfer and Hans Peter Schmid and Narasinha Shurpali and Oliver Sonnentag and Angela C I Tang and Masahito Ueyama and Rodrigo Vargas and Timo Vesala and Eric J Ward and Lisamarie Windham-Myers and Georg Wohlfahrt and Donatella Zona},
url = {https://doi.org/10.1175/BAMS-D-18-0268.1},
doi = {10.1175/BAMS-D-18-0268.1},
year = {2019},
date = {2019-12-01},
journal = {Bulletin of the American Meteorological Society},
volume = {100},
number = {12},
pages = {2607-2632},
publisher = {American Meteorological Society},
address = {Boston MA, USA},
abstract = {This paper describes the formation of, and initial results for, a new FLUXNET coordination network for ecosystem-scale methane (CH4) measurements at 60 sites globally, organized by the Global Carbon Project in partnership with other initiatives and regional flux tower networks. The objectives of the effort are presented along with an overview of the coverage of eddy covariance (EC) CH4 flux measurements globally, initial results comparing CH4 fluxes across the sites, and future research directions and needs. Annual estimates of net CH4 fluxes across sites ranged from −0.2 ± 0.02 g C m–2 yr–1 for an upland forest site to 114.9 ± 13.4 g C m–2 yr–1 for an estuarine freshwater marsh, with fluxes exceeding 40 g C m–2 yr–1 at multiple sites. Average annual soil and air temperatures were found to be the strongest predictor of annual CH4 flux across wetland sites globally. Water table position was positively correlated with annual CH4 emissions, although only for wetland sites that were not consistently inundated throughout the year. The ratio of annual CH4 fluxes to ecosystem respiration increased significantly with mean site temperature. Uncertainties in annual CH4 estimates due to gap-filling and random errors were on average ±1.6 g C m–2 yr–1 at 95% confidence, with the relative error decreasing exponentially with increasing flux magnitude across sites. Through the analysis and synthesis of a growing EC CH4 flux database, the controls on ecosystem CH4 fluxes can be better understood, used to inform and validate Earth system models, and reconcile differences between land surface model- and atmospheric-based estimates of CH4 emissions.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper describes the formation of, and initial results for, a new FLUXNET coordination network for ecosystem-scale methane (CH4) measurements at 60 sites globally, organized by the Global Carbon Project in partnership with other initiatives and regional flux tower networks. The objectives of the effort are presented along with an overview of the coverage of eddy covariance (EC) CH4 flux measurements globally, initial results comparing CH4 fluxes across the sites, and future research directions and needs. Annual estimates of net CH4 fluxes across sites ranged from −0.2 ± 0.02 g C m–2 yr–1 for an upland forest site to 114.9 ± 13.4 g C m–2 yr–1 for an estuarine freshwater marsh, with fluxes exceeding 40 g C m–2 yr–1 at multiple sites. Average annual soil and air temperatures were found to be the strongest predictor of annual CH4 flux across wetland sites globally. Water table position was positively correlated with annual CH4 emissions, although only for wetland sites that were not consistently inundated throughout the year. The ratio of annual CH4 fluxes to ecosystem respiration increased significantly with mean site temperature. Uncertainties in annual CH4 estimates due to gap-filling and random errors were on average ±1.6 g C m–2 yr–1 at 95% confidence, with the relative error decreasing exponentially with increasing flux magnitude across sites. Through the analysis and synthesis of a growing EC CH4 flux database, the controls on ecosystem CH4 fluxes can be better understood, used to inform and validate Earth system models, and reconcile differences between land surface model- and atmospheric-based estimates of CH4 emissions. |
Orland, Ian J; He, Feng; Bar-Matthews, Miryam; Chen, Guangshan; Ayalon, Avner; Kutzbach, John E: Resolving seasonal rainfall changes in the Middle East during the last interglacial period. In: Proceedings of the National Academy of Sciences, vol. 116, no. 50, pp. 24985-24990, 2019, ISSN: 0027-8424. @article{Orland24985,
title = {Resolving seasonal rainfall changes in the Middle East during the last interglacial period},
author = {Ian J Orland and Feng He and Miryam Bar-Matthews and Guangshan Chen and Avner Ayalon and John E Kutzbach},
url = {https://www.pnas.org/content/116/50/24985},
doi = {10.1073/pnas.1903139116},
issn = {0027-8424},
year = {2019},
date = {2019-11-25},
journal = {Proceedings of the National Academy of Sciences},
volume = {116},
number = {50},
pages = {24985-24990},
publisher = {National Academy of Sciences},
abstract = {The Middle East was a gateway for early human migration out of Africa, and it is likely that the regiontextquoterights climate played an important role in this anthropogenic transition. This study is motivated by conflicting interpretations of rainfall seasonality from regional paleoenvironmental records. Specifically, we address whether summer monsoon rainfall may have expanded northward into the Middle East in the past. Today, the region has dry summers and relatively wet winters; the northern limit of the modern monsoon is far to the south. Here, we combine climate modeling with seasonal-resolution geochemical analysis of cave carbonates from Israel and find evidence for summer monsoon rainfall during recurrent intervals of the last interglacial period, which overlaps with archeological indicators of human migration.Paleorainfall proxy records from the Middle East have revealed remarkable patterns of variability since the penultimate glacial period (140 ka), but the seasonality of this signal has been unresolvable. Here, seasonal-resolution oxygen isotope data from Soreq Cave speleothems suggest that summer monsoon rainfall periodically reaches as far north as Israel—well removed from the modern monsoon—at times (~125, 105 ka) that overlap with evidence for some of the earliest modern human migrations out of Africa. These seasonal proxy data are corroborated by seasonal-resolution model output of the amount and oxygen-isotope ratio of rainfall from an isotope-enabled climate model. In contrast to the modern regional climate where rainfall is delivered predominantly in winter months along westerly storm tracks, the model suggests that during extreme peaks of summer insolation—as occurs during the last interglacial (e.g., 125, 105 ka)—regional rainfall increases due to both wetter winters and the incursion of summer monsoons. This interpretation brings clarity to regional paleoproxy records and provides important environmental context along one potential pathway of early modern human migration.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The Middle East was a gateway for early human migration out of Africa, and it is likely that the regiontextquoterights climate played an important role in this anthropogenic transition. This study is motivated by conflicting interpretations of rainfall seasonality from regional paleoenvironmental records. Specifically, we address whether summer monsoon rainfall may have expanded northward into the Middle East in the past. Today, the region has dry summers and relatively wet winters; the northern limit of the modern monsoon is far to the south. Here, we combine climate modeling with seasonal-resolution geochemical analysis of cave carbonates from Israel and find evidence for summer monsoon rainfall during recurrent intervals of the last interglacial period, which overlaps with archeological indicators of human migration.Paleorainfall proxy records from the Middle East have revealed remarkable patterns of variability since the penultimate glacial period (140 ka), but the seasonality of this signal has been unresolvable. Here, seasonal-resolution oxygen isotope data from Soreq Cave speleothems suggest that summer monsoon rainfall periodically reaches as far north as Israel—well removed from the modern monsoon—at times (~125, 105 ka) that overlap with evidence for some of the earliest modern human migrations out of Africa. These seasonal proxy data are corroborated by seasonal-resolution model output of the amount and oxygen-isotope ratio of rainfall from an isotope-enabled climate model. In contrast to the modern regional climate where rainfall is delivered predominantly in winter months along westerly storm tracks, the model suggests that during extreme peaks of summer insolation—as occurs during the last interglacial (e.g., 125, 105 ka)—regional rainfall increases due to both wetter winters and the incursion of summer monsoons. This interpretation brings clarity to regional paleoproxy records and provides important environmental context along one potential pathway of early modern human migration. |
Donnelly, Alison; Yu, Rong; Liu, Lingling; Hanes, Jonathan M; Liang, Liang; Schwartz, Mark D; Desai, Ankur R: Comparing in-situ leaf observations in early spring with flux tower CO2 exchange, MODIS EVI and modeled LAI in a northern mixed forest. In: Agricultural and Forest Meteorology, vol. 278, pp. 107673, 2019, ISSN: 0168-1923. @article{DONNELLY2019107673,
title = {Comparing in-situ leaf observations in early spring with flux tower CO2 exchange, MODIS EVI and modeled LAI in a northern mixed forest},
author = {Alison Donnelly and Rong Yu and Lingling Liu and Jonathan M Hanes and Liang Liang and Mark D Schwartz and Ankur R Desai},
url = {https://www.sciencedirect.com/science/article/pii/S0168192319302874},
doi = {https://doi.org/10.1016/j.agrformet.2019.107673},
issn = {0168-1923},
year = {2019},
date = {2019-11-15},
journal = {Agricultural and Forest Meteorology},
volume = {278},
pages = {107673},
abstract = {Changes in the timing and duration of spring leaf development have implications for the start of the carbon uptake period and are therefore fundamental to the accurate calculation of carbon budgets, and in determining the potential for forests to sequester CO2. Here, we examined trends in CO2 exchange (Net Ecosystem Exchange (NEE), Gross Primary Production (GPP) and Ecosystem Respiration (ER)) (1997–2016) and satellite derived measures (Enhanced Vegetation Index (EVI) and modeled Leaf Area Index (LAI)) of the start of spring from the MODIS product MOD13Q1 (2001–2016) for a mixed forest landscape in northern Wisconsin, USA. We then explored the relationship between these indirect determinants of spring phenology and the timing and duration of spring phenophases (bud-burst, leaf-out, full-leaf unfolded) of trees over a 5-year period (2006–2010). Contrary to earlier studies focus’, our analysis did not find a consistent link between the early transition, of the forest stand from C source to sink with increased annual productivity. Interestingly, while annual regional NEE trended from a source to a sink over the study period, there were no significant concomitant trends in the timing of the start of the season, peak season or the duration of the season derived from (i) satellite data (2001–2016), (ii) flux data (1997–2016) nor from in situ observations (2006–2010). The range of time periods used and difference in phenological determinants examined likely contributed to a lack of expected relationships. The results highlight the need for in situ observations of different forest layers, in particular shrubs, which could help explain current discrepancies between direct and indirect determinants of spring phenology. Furthermore, characterization of abiotic influences on C flux measurements may further explain some of the observed discrepancies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Changes in the timing and duration of spring leaf development have implications for the start of the carbon uptake period and are therefore fundamental to the accurate calculation of carbon budgets, and in determining the potential for forests to sequester CO2. Here, we examined trends in CO2 exchange (Net Ecosystem Exchange (NEE), Gross Primary Production (GPP) and Ecosystem Respiration (ER)) (1997–2016) and satellite derived measures (Enhanced Vegetation Index (EVI) and modeled Leaf Area Index (LAI)) of the start of spring from the MODIS product MOD13Q1 (2001–2016) for a mixed forest landscape in northern Wisconsin, USA. We then explored the relationship between these indirect determinants of spring phenology and the timing and duration of spring phenophases (bud-burst, leaf-out, full-leaf unfolded) of trees over a 5-year period (2006–2010). Contrary to earlier studies focus’, our analysis did not find a consistent link between the early transition, of the forest stand from C source to sink with increased annual productivity. Interestingly, while annual regional NEE trended from a source to a sink over the study period, there were no significant concomitant trends in the timing of the start of the season, peak season or the duration of the season derived from (i) satellite data (2001–2016), (ii) flux data (1997–2016) nor from in situ observations (2006–2010). The range of time periods used and difference in phenological determinants examined likely contributed to a lack of expected relationships. The results highlight the need for in situ observations of different forest layers, in particular shrubs, which could help explain current discrepancies between direct and indirect determinants of spring phenology. Furthermore, characterization of abiotic influences on C flux measurements may further explain some of the observed discrepancies. |
Turner, Jessica; Desai, Ankur R; Thom, Jonathan; Wickland, Kimberly P; Olson, Brent: Wind Sheltering Impacts on Land-Atmosphere Fluxes Over Fens. In: Frontiers in Environmental Science, vol. 7, pp. 179, 2019, ISSN: 2296-665X. @article{10.3389/fenvs.2019.00179,
title = {Wind Sheltering Impacts on Land-Atmosphere Fluxes Over Fens},
author = {Jessica Turner and Ankur R Desai and Jonathan Thom and Kimberly P Wickland and Brent Olson},
url = {https://www.frontiersin.org/article/10.3389/fenvs.2019.00179},
doi = {10.3389/fenvs.2019.00179},
issn = {2296-665X},
year = {2019},
date = {2019-11-13},
journal = {Frontiers in Environmental Science},
volume = {7},
pages = {179},
abstract = {Wetlands and their ability to mitigate climate change motivates restorative and protective action; however, scientific understanding of land-atmosphere interactions is restricted by our limited continuous observations of gaseous fluxes. Many wetlands are small in spatial scale and embedded in forested landscapes. Yet, little is known about how the relative sheltering of forests affects net carbon (C) and energy balance. Here, we analyze coterminous USGS and Ameriflux eddy covariance flux tower observations over 3 years in two shrub fens in Northern Wisconsin, one more sheltered (US-ALQ) than the other (US-Los). Unsurprisingly, the open site showed higher overall wind speeds. This should have implications for atmospheric fluxes in wetlands as wind-forced processes are essential in promoting gas exchange over water. While both sites had similar half-hourly net ecosystem exchange of CO2 (NEE) during daytime, there were significant differences in nighttime NEE, as well as in net radiation partitioning in early spring and late summer. Sensible heat (H) fluxes were smaller at the sheltered fen except for the months of July–September. In contrast, latent heat (LE) fluxes were higher in every month except July. Additionally, sheltered fen ecosystem respiration had a weaker linear correlation with air temperature (R: 0.08 vs. 0.57 for the open fen). Our work suggests that canopy sheltering does not cause significant differences in half-hourly NEE during the day, but rather the largest differences such as lower CO2 emissions occur at nighttime due to higher variance at very low wind speeds. Sheltering also influenced direction of air flow, mean wind speeds in day vs. night, energy balance, and sensible and latent heat fluxes. We discuss implications of these findings for wetland restoration.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Wetlands and their ability to mitigate climate change motivates restorative and protective action; however, scientific understanding of land-atmosphere interactions is restricted by our limited continuous observations of gaseous fluxes. Many wetlands are small in spatial scale and embedded in forested landscapes. Yet, little is known about how the relative sheltering of forests affects net carbon (C) and energy balance. Here, we analyze coterminous USGS and Ameriflux eddy covariance flux tower observations over 3 years in two shrub fens in Northern Wisconsin, one more sheltered (US-ALQ) than the other (US-Los). Unsurprisingly, the open site showed higher overall wind speeds. This should have implications for atmospheric fluxes in wetlands as wind-forced processes are essential in promoting gas exchange over water. While both sites had similar half-hourly net ecosystem exchange of CO2 (NEE) during daytime, there were significant differences in nighttime NEE, as well as in net radiation partitioning in early spring and late summer. Sensible heat (H) fluxes were smaller at the sheltered fen except for the months of July–September. In contrast, latent heat (LE) fluxes were higher in every month except July. Additionally, sheltered fen ecosystem respiration had a weaker linear correlation with air temperature (R: 0.08 vs. 0.57 for the open fen). Our work suggests that canopy sheltering does not cause significant differences in half-hourly NEE during the day, but rather the largest differences such as lower CO2 emissions occur at nighttime due to higher variance at very low wind speeds. Sheltering also influenced direction of air flow, mean wind speeds in day vs. night, energy balance, and sensible and latent heat fluxes. We discuss implications of these findings for wetland restoration. |
Salonen, Sakari J; Korpela, Mikko; Williams, John W; Luoto, Miska: Machine-learning based reconstructions of primary and secondary climate variables from North American and European fossil pollen data. In: Scientific Reports, vol. 9, no. 1, pp. 15805, 2019, ISSN: 2045-2322. @article{Salonen2019,
title = {Machine-learning based reconstructions of primary and secondary climate variables from North American and European fossil pollen data},
author = {Sakari J Salonen and Mikko Korpela and John W Williams and Miska Luoto},
url = {https://www.nature.com/articles/s41598-019-52293-4},
doi = {10.1038/s41598-019-52293-4},
issn = {2045-2322},
year = {2019},
date = {2019-11-01},
journal = {Scientific Reports},
volume = {9},
number = {1},
pages = {15805},
abstract = {We test several quantitative algorithms as palaeoclimate reconstruction tools for North American and European fossil pollen data, using both classical methods and newer machine-learning approaches based on regression tree ensembles and artificial neural networks. We focus on the reconstruction of secondary climate variables (here, January temperature and annual water balance), as their comparatively small ecological influence compared to the primary variable (July temperature) presents special challenges to palaeo-reconstructions. We test the pollen--climate models using a novel and comprehensive cross-validation approach, running a series of h-block cross-validations using h values of 100--1500thinspacekm. Our study illustrates major benefits of this variable h-block cross-validation scheme, as the effect of spatial autocorrelation is minimized, while the cross-validations with increasing h values can reveal instabilities in the calibration model and approximate challenges faced in palaeo-reconstructions with poor modern analogues. We achieve well-performing calibration models for both primary and secondary climate variables, with boosted regression trees providing the overall most robust performance, while the palaeoclimate reconstructions from fossil datasets show major independent features for the primary and secondary variables. Our results suggest that with careful variable selection and consideration of ecological processes, robust reconstruction of both primary and secondary climate variables is possible.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We test several quantitative algorithms as palaeoclimate reconstruction tools for North American and European fossil pollen data, using both classical methods and newer machine-learning approaches based on regression tree ensembles and artificial neural networks. We focus on the reconstruction of secondary climate variables (here, January temperature and annual water balance), as their comparatively small ecological influence compared to the primary variable (July temperature) presents special challenges to palaeo-reconstructions. We test the pollen--climate models using a novel and comprehensive cross-validation approach, running a series of h-block cross-validations using h values of 100--1500thinspacekm. Our study illustrates major benefits of this variable h-block cross-validation scheme, as the effect of spatial autocorrelation is minimized, while the cross-validations with increasing h values can reveal instabilities in the calibration model and approximate challenges faced in palaeo-reconstructions with poor modern analogues. We achieve well-performing calibration models for both primary and secondary climate variables, with boosted regression trees providing the overall most robust performance, while the palaeoclimate reconstructions from fossil datasets show major independent features for the primary and secondary variables. Our results suggest that with careful variable selection and consideration of ecological processes, robust reconstruction of both primary and secondary climate variables is possible. |
Wang, Fuyao; Vavrus, Stephen J; Francis, Jennifer A; Martin, Jonathan E: The role of horizontal thermal advection in regulating wintertime mean and extreme temperatures over interior North America during the past and future. In: Climate Dynamics, vol. 53, no. 9, pp. 6125-6144, 2019, ISSN: 1432-0894. @article{Wang2019,
title = {The role of horizontal thermal advection in regulating wintertime mean and extreme temperatures over interior North America during the past and future},
author = {Fuyao Wang and Stephen J Vavrus and Jennifer A Francis and Jonathan E Martin},
url = {https://doi.org/10.1007/s00382-019-04917-8},
doi = {10.1007/s00382-019-04917-8},
issn = {1432-0894},
year = {2019},
date = {2019-11-01},
journal = {Climate Dynamics},
volume = {53},
number = {9},
pages = {6125-6144},
abstract = {Horizontal thermal advection plays an especially prominent role in affecting winter climate over continental interiors, where both climatological conditions and extreme weather are strongly regulated by transport of remote air masses. Interior North America is one such region, and it experiences occasional cold-air outbreaks (CAOs) that may be related to amplified Arctic warming. Despite the known importance of dynamics in shaping the winter climate of this sector and the potential for climate change to modify heat transport, limited attention has been paid to the regional impact of thermal advection. Here, we use a reanalysis product and output from the Community Earth System Model's Large Ensemble to quantify the roles of zonal and meridional temperature advection over the central United States during winter, both in the late twentieth and late twenty-first centuries. We frame our findings as a ``tug-of-war'' between opposing influences of the two advection components and between these dynamical forcings vs. thermodynamic changes under greenhouse warming. During both historical and future periods, zonal temperature advection is stronger than meridional advection east of the Rockies. The model simulates a future weakening of both zonal and meridional temperature advection, such that westerly flow provides less warming and northerly flow less cooling. On the most extreme cold days, meridional cold-air advection is more important than zonal warm-air advection. CAOs in the future feature stronger northerly flow but less extreme temperatures (even relative to the warmer climate), indicating the importance of other mechanisms such as snow cover and sea ice changes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Horizontal thermal advection plays an especially prominent role in affecting winter climate over continental interiors, where both climatological conditions and extreme weather are strongly regulated by transport of remote air masses. Interior North America is one such region, and it experiences occasional cold-air outbreaks (CAOs) that may be related to amplified Arctic warming. Despite the known importance of dynamics in shaping the winter climate of this sector and the potential for climate change to modify heat transport, limited attention has been paid to the regional impact of thermal advection. Here, we use a reanalysis product and output from the Community Earth System Model's Large Ensemble to quantify the roles of zonal and meridional temperature advection over the central United States during winter, both in the late twentieth and late twenty-first centuries. We frame our findings as a ``tug-of-war'' between opposing influences of the two advection components and between these dynamical forcings vs. thermodynamic changes under greenhouse warming. During both historical and future periods, zonal temperature advection is stronger than meridional advection east of the Rockies. The model simulates a future weakening of both zonal and meridional temperature advection, such that westerly flow provides less warming and northerly flow less cooling. On the most extreme cold days, meridional cold-air advection is more important than zonal warm-air advection. CAOs in the future feature stronger northerly flow but less extreme temperatures (even relative to the warmer climate), indicating the importance of other mechanisms such as snow cover and sea ice changes. |
Giuliani, Matteo; Zaniolo, Marta; Castelletti, Andrea; Davoli, Guido; Block, Paul: Detecting the State of the Climate System via Artificial Intelligence to Improve Seasonal Forecasts and Inform Reservoir Operations. In: Water Resources Research, vol. 55, no. 11, pp. 9133-9147, 2019. @article{Giuliani2019,
title = {Detecting the State of the Climate System via Artificial Intelligence to Improve Seasonal Forecasts and Inform Reservoir Operations},
author = {Matteo Giuliani and Marta Zaniolo and Andrea Castelletti and Guido Davoli and Paul Block},
url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2019WR025035},
doi = {https://doi.org/10.1029/2019WR025035},
year = {2019},
date = {2019-10-20},
journal = {Water Resources Research},
volume = {55},
number = {11},
pages = {9133-9147},
abstract = {Abstract Increasingly variable hydrologic regimes combined with more frequent and intense extreme events are challenging water systems management worldwide. These trends emphasize the need of accurate medium- to long-term predictions to timely prompt anticipatory operations. Despite in some locations global climate oscillations and particularly the El Niño Southern Oscillation (ENSO) may contribute to extending forecast lead times, in other regions there is no consensus on how ENSO can be detected, and used as local conditions are also influenced by other concurrent climate signals. In this work, we introduce the Climate State Intelligence framework to capture the state of multiple global climate signals via artificial intelligence and improve seasonal forecasts. These forecasts are used as additional inputs for informing water system operations and their value is quantified as the corresponding gain in system performance. We apply the framework to the Lake Como basin, a regulated lake in northern Italy mainly operated for flood control and irrigation supply. Numerical results show the existence of notable teleconnection patterns dependent on both ENSO and the North Atlantic Oscillation over the Alpine region, which contribute in generating skilful seasonal precipitation and hydrologic forecasts. The use of this information for conditioning the lake operations produces an average 44% improvement in system performance with respect to a baseline solution not informed by any forecast, with this gain that further increases during extreme drought episodes. Our results also suggest that observed preseason sea surface temperature anomalies appear more valuable than hydrologic-based seasonal forecasts, producing an average 59% improvement in system performance.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Abstract Increasingly variable hydrologic regimes combined with more frequent and intense extreme events are challenging water systems management worldwide. These trends emphasize the need of accurate medium- to long-term predictions to timely prompt anticipatory operations. Despite in some locations global climate oscillations and particularly the El Niño Southern Oscillation (ENSO) may contribute to extending forecast lead times, in other regions there is no consensus on how ENSO can be detected, and used as local conditions are also influenced by other concurrent climate signals. In this work, we introduce the Climate State Intelligence framework to capture the state of multiple global climate signals via artificial intelligence and improve seasonal forecasts. These forecasts are used as additional inputs for informing water system operations and their value is quantified as the corresponding gain in system performance. We apply the framework to the Lake Como basin, a regulated lake in northern Italy mainly operated for flood control and irrigation supply. Numerical results show the existence of notable teleconnection patterns dependent on both ENSO and the North Atlantic Oscillation over the Alpine region, which contribute in generating skilful seasonal precipitation and hydrologic forecasts. The use of this information for conditioning the lake operations produces an average 44% improvement in system performance with respect to a baseline solution not informed by any forecast, with this gain that further increases during extreme drought episodes. Our results also suggest that observed preseason sea surface temperature anomalies appear more valuable than hydrologic-based seasonal forecasts, producing an average 59% improvement in system performance. |
Khider, D; Emile-Geay, J; McKay, N P; Gil, Y; Garijo, D; Ratnakar, V; Alonso-Garcia, M; Bertrand, S; Bothe, O; Brewer, P; Bunn, A; Chevalier, M; Comas-Bru, L; Csank, A; Dassié, E; DeLong, K; Felis, T; Francus, P; Frappier, A; Gray, W; Goring, S; Jonkers, L; Kahle, M; Kaufman, D; Kehrwald, N M; Martrat, B; McGregor, H; Richey, J; Schmittner, A; Scroxton, N; Sutherland, E; Thirumalai, K; Allen, K; Arnaud, F; Axford, Y; Barrows, T; Bazin, L; Birch, S E Pilaar; Bradley, E; Bregy, J; Capron, E; Cartapanis, O; Chiang, H -W; Cobb, K M; Debret, M; Dommain, R; Du, J; Dyez, K; Emerick, S; Erb, M P; Falster, G; Finsinger, W; Fortier, D; Gauthier, Nicolas; George, S; Grimm, E; Hertzberg, J; Hibbert, F; Hillman, A; Hobbs, W; Huber, M; Hughes, A L C; Jaccard, S; Ruan, J; Kienast, M; Konecky, B; Roux, G Le; Lyubchich, V; Novello, V F; Olaka, L; Partin, J W; Pearce, C; Phipps, S J; Pignol, C; Piotrowska, N; Poli, M -S; Prokopenko, A; Schwanck, F; Stepanek, C; Swann, G E A; Telford, R; Thomas, E; Thomas, Z; Truebe, S; von Gunten, L; Waite, A; Weitzel, N; Wilhelm, B; Williams, J; Williams, J J; Winstrup, M; Zhao, N; Zhou, Y: PaCTS 1.0: A Crowdsourced Reporting Standard for Paleoclimate Data. In: Paleoceanography and Paleoclimatology, vol. 34, no. 10, pp. 1570-1596, 2019. @article{https://doi.org/10.1029/2019PA003632,
title = {PaCTS 1.0: A Crowdsourced Reporting Standard for Paleoclimate Data},
author = {D Khider and J Emile-Geay and N P McKay and Y Gil and D Garijo and V Ratnakar and M Alonso-Garcia and S Bertrand and O Bothe and P Brewer and A Bunn and M Chevalier and L Comas-Bru and A Csank and E Dassié and K DeLong and T Felis and P Francus and A Frappier and W Gray and S Goring and L Jonkers and M Kahle and D Kaufman and N M Kehrwald and B Martrat and H McGregor and J Richey and A Schmittner and N Scroxton and E Sutherland and K Thirumalai and K Allen and F Arnaud and Y Axford and T Barrows and L Bazin and S E Pilaar Birch and E Bradley and J Bregy and E Capron and O Cartapanis and H -W Chiang and K M Cobb and M Debret and R Dommain and J Du and K Dyez and S Emerick and M P Erb and G Falster and W Finsinger and D Fortier and Nicolas Gauthier and S George and E Grimm and J Hertzberg and F Hibbert and A Hillman and W Hobbs and M Huber and A L C Hughes and S Jaccard and J Ruan and M Kienast and B Konecky and G Le Roux and V Lyubchich and V F Novello and L Olaka and J W Partin and C Pearce and S J Phipps and C Pignol and N Piotrowska and M -S Poli and A Prokopenko and F Schwanck and C Stepanek and G E A Swann and R Telford and E Thomas and Z Thomas and S Truebe and L von Gunten and A Waite and N Weitzel and B Wilhelm and J Williams and J J Williams and M Winstrup and N Zhao and Y Zhou},
url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2019PA003632},
doi = {https://doi.org/10.1029/2019PA003632},
year = {2019},
date = {2019-09-03},
journal = {Paleoceanography and Paleoclimatology},
volume = {34},
number = {10},
pages = {1570-1596},
abstract = {Abstract The progress of science is tied to the standardization of measurements, instruments, and data. This is especially true in the Big Data age, where analyzing large data volumes critically hinges on the data being standardized. Accordingly, the lack of community-sanctioned data standards in paleoclimatology has largely precluded the benefits of Big Data advances in the field. Building upon recent efforts to standardize the format and terminology of paleoclimate data, this article describes the Paleoclimate Community reporTing Standard (PaCTS), a crowdsourced reporting standard for such data. PaCTS captures which information should be included when reporting paleoclimate data, with the goal of maximizing the reuse value of paleoclimate data sets, particularly for synthesis work and comparison to climate model simulations. Initiated by the LinkedEarth project, the process to elicit a reporting standard involved an international workshop in 2016, various forms of digital community engagement over the next few years, and grassroots working groups. Participants in this process identified important properties across paleoclimate archives, in addition to the reporting of uncertainties and chronologies; they also identified archive-specific properties and distinguished reporting standards for new versus legacy data sets. This work shows that at least 135 respondents overwhelmingly support a drastic increase in the amount of metadata accompanying paleoclimate data sets. Since such goals are at odds with present practices, we discuss a transparent path toward implementing or revising these recommendations in the near future, using both bottom-up and top-down approaches.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Abstract The progress of science is tied to the standardization of measurements, instruments, and data. This is especially true in the Big Data age, where analyzing large data volumes critically hinges on the data being standardized. Accordingly, the lack of community-sanctioned data standards in paleoclimatology has largely precluded the benefits of Big Data advances in the field. Building upon recent efforts to standardize the format and terminology of paleoclimate data, this article describes the Paleoclimate Community reporTing Standard (PaCTS), a crowdsourced reporting standard for such data. PaCTS captures which information should be included when reporting paleoclimate data, with the goal of maximizing the reuse value of paleoclimate data sets, particularly for synthesis work and comparison to climate model simulations. Initiated by the LinkedEarth project, the process to elicit a reporting standard involved an international workshop in 2016, various forms of digital community engagement over the next few years, and grassroots working groups. Participants in this process identified important properties across paleoclimate archives, in addition to the reporting of uncertainties and chronologies; they also identified archive-specific properties and distinguished reporting standards for new versus legacy data sets. This work shows that at least 135 respondents overwhelmingly support a drastic increase in the amount of metadata accompanying paleoclimate data sets. Since such goals are at odds with present practices, we discuss a transparent path toward implementing or revising these recommendations in the near future, using both bottom-up and top-down approaches. |
Peltola, O; Vesala, T; Gao, Y; Räty, O; Alekseychik, P; Aurela, M; Chojnicki, B; Desai, A R; Dolman, A J; Euskirchen, E S; Friborg, T; Göckede, M; Helbig, M; Humphreys, E; Jackson, R B; Jocher, G; Joos, F; Klatt, J; Knox, S H; Kowalska, N; Kutzbach, L; Lienert, S; Lohila, A; Mammarella, I; Nadeau, D F; Nilsson, M B; Oechel, W C; Peichl, M; Pypker, T; Quinton, W; Rinne, J; Sachs, T; Samson, M; Schmid, H P; Sonnentag, O; Wille, C; Zona, D; Aalto, T: Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations. In: Earth System Science Data, vol. 11, no. 3, pp. 1263-1289, 2019. @article{essd-11-1263-2019,
title = {Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations},
author = {O Peltola and T Vesala and Y Gao and O Räty and P Alekseychik and M Aurela and B Chojnicki and A R Desai and A J Dolman and E S Euskirchen and T Friborg and M Göckede and M Helbig and E Humphreys and R B Jackson and G Jocher and F Joos and J Klatt and S H Knox and N Kowalska and L Kutzbach and S Lienert and A Lohila and I Mammarella and D F Nadeau and M B Nilsson and W C Oechel and M Peichl and T Pypker and W Quinton and J Rinne and T Sachs and M Samson and H P Schmid and O Sonnentag and C Wille and D Zona and T Aalto},
url = {https://essd.copernicus.org/articles/11/1263/2019/},
doi = {10.5194/essd-11-1263-2019},
year = {2019},
date = {2019-08-22},
journal = {Earth System Science Data},
volume = {11},
number = {3},
pages = {1263-1289},
abstract = {Natural wetlands constitute the largest and most uncertain source of methane (CH4) to the atmosphere and a large fraction of them are found in the northern latitudes. These emissions are typically estimated using process (“bottom-up”) or inversion (“top-down”) models. However, estimates from these two types of models are not independent of each other since the top-down estimates usually rely on the a priori estimation of these emissions obtained with process models. Hence, independent spatially explicit validation data are needed. Here we utilize a random forest (RF) machine-learning technique to upscale CH4 eddy covariance flux measurements from 25 sites to estimate CH4 wetland emissions from the northern latitudes (north of 45∘ N). Eddy covariance data from 2005 to 2016 are used for model development. The model is then used to predict emissions during 2013 and 2014. The predictive performance of the RF model is evaluated using a leave-one-site-out cross-validation scheme. The performance (Nash–Sutcliffe model efficiency =0.47) is comparable to previous studies upscaling net ecosystem exchange of carbon dioxide and studies comparing process model output against site-level CH4 emission data. The global distribution of wetlands is one major source of uncertainty for upscaling CH4. Thus, three wetland distribution maps are utilized in the upscaling. Depending on the wetland distribution map, the annual emissions for the northern wetlands yield 32 (22.3–41.2, 95 % confidence interval calculated from a RF model ensemble), 31 (21.4–39.9) or 38 (25.9–49.5) Tg(CH4) yr−1. To further evaluate the uncertainties of the upscaled CH4 flux data products we also compared them against output from two process models (LPX-Bern and WetCHARTs), and methodological issues related to CH4 flux upscaling are discussed.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Natural wetlands constitute the largest and most uncertain source of methane (CH4) to the atmosphere and a large fraction of them are found in the northern latitudes. These emissions are typically estimated using process (“bottom-up”) or inversion (“top-down”) models. However, estimates from these two types of models are not independent of each other since the top-down estimates usually rely on the a priori estimation of these emissions obtained with process models. Hence, independent spatially explicit validation data are needed. Here we utilize a random forest (RF) machine-learning technique to upscale CH4 eddy covariance flux measurements from 25 sites to estimate CH4 wetland emissions from the northern latitudes (north of 45∘ N). Eddy covariance data from 2005 to 2016 are used for model development. The model is then used to predict emissions during 2013 and 2014. The predictive performance of the RF model is evaluated using a leave-one-site-out cross-validation scheme. The performance (Nash–Sutcliffe model efficiency =0.47) is comparable to previous studies upscaling net ecosystem exchange of carbon dioxide and studies comparing process model output against site-level CH4 emission data. The global distribution of wetlands is one major source of uncertainty for upscaling CH4. Thus, three wetland distribution maps are utilized in the upscaling. Depending on the wetland distribution map, the annual emissions for the northern wetlands yield 32 (22.3–41.2, 95 % confidence interval calculated from a RF model ensemble), 31 (21.4–39.9) or 38 (25.9–49.5) Tg(CH4) yr−1. To further evaluate the uncertainties of the upscaled CH4 flux data products we also compared them against output from two process models (LPX-Bern and WetCHARTs), and methodological issues related to CH4 flux upscaling are discussed. |
Holland, Marika M; Landrum, Laura; Bailey, David; Vavrus, Steve: Changing Seasonal Predictability of Arctic Summer Sea Ice Area in a Warming Climate. In: Journal of Climate, vol. 32, no. 16, pp. 4963-4979, 2019. @article{Holland15Aug.2019,
title = {Changing Seasonal Predictability of Arctic Summer Sea Ice Area in a Warming Climate},
author = {Marika M Holland and Laura Landrum and David Bailey and Steve Vavrus},
url = {https://doi.org/10.1175/JCLI-D-19-0034.1},
doi = {10.1175/JCLI-D-19-0034.1},
year = {2019},
date = {2019-08-15},
journal = {Journal of Climate},
volume = {32},
number = {16},
pages = {4963-4979},
publisher = {American Meteorological Society},
address = {Boston MA, USA},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Dawson, Andria; Paciorek, Christopher J; Goring, Simon J; Jackson, Stephen T; McLachlan, Jason S; Williams, John W: Quantifying trends and uncertainty in prehistoric forest composition in the upper Midwestern United States. In: Ecology, vol. 100, no. 12, pp. e02856, 2019. @article{https://doi.org/10.1002/ecy.2856,
title = {Quantifying trends and uncertainty in prehistoric forest composition in the upper Midwestern United States},
author = {Andria Dawson and Christopher J Paciorek and Simon J Goring and Stephen T Jackson and Jason S McLachlan and John W Williams},
url = {https://esajournals.onlinelibrary.wiley.com/doi/abs/10.1002/ecy.2856},
doi = {https://doi.org/10.1002/ecy.2856},
year = {2019},
date = {2019-08-05},
journal = {Ecology},
volume = {100},
number = {12},
pages = {e02856},
abstract = {Abstract Forest ecosystems in eastern North America have been in flux for the last several thousand years, well before Euro-American land clearance and the 20th-century onset of anthropogenic climate change. However, the magnitude and uncertainty of prehistoric vegetation change have been difficult to quantify because of the multiple ecological, dispersal, and sedimentary processes that govern the relationship between forest composition and fossil pollen assemblages. Here we extend STEPPS, a Bayesian hierarchical spatiotemporal pollen–vegetation model, to estimate changes in forest composition in the upper Midwestern United States from about 2,100 to 300 yr ago. Using this approach, we find evidence for large changes in the relative abundance of some species, and significant changes in community composition. However, these changes took place against a regional background of changes that were small in magnitude or not statistically significant, suggesting complexity in the spatiotemporal patterns of forest dynamics. The single largest change is the infilling of Tsuga canadensis in northern Wisconsin over the past 2,000 yr. Despite range infilling, the range limit of T. canadensis was largely stable, with modest expansion westward. The regional ecotone between temperate hardwood forests and northern mixed hardwood/conifer forests shifted southwestward by 15–20 km in Minnesota and northwestern Wisconsin. Fraxinus, Ulmus, and other mesic hardwoods expanded in the Big Woods region of southern Minnesota. The increasing density of paleoecological data networks and advances in statistical modeling approaches now enables the confident detection of subtle but significant changes in forest composition over the last 2,000 yr.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Abstract Forest ecosystems in eastern North America have been in flux for the last several thousand years, well before Euro-American land clearance and the 20th-century onset of anthropogenic climate change. However, the magnitude and uncertainty of prehistoric vegetation change have been difficult to quantify because of the multiple ecological, dispersal, and sedimentary processes that govern the relationship between forest composition and fossil pollen assemblages. Here we extend STEPPS, a Bayesian hierarchical spatiotemporal pollen–vegetation model, to estimate changes in forest composition in the upper Midwestern United States from about 2,100 to 300 yr ago. Using this approach, we find evidence for large changes in the relative abundance of some species, and significant changes in community composition. However, these changes took place against a regional background of changes that were small in magnitude or not statistically significant, suggesting complexity in the spatiotemporal patterns of forest dynamics. The single largest change is the infilling of Tsuga canadensis in northern Wisconsin over the past 2,000 yr. Despite range infilling, the range limit of T. canadensis was largely stable, with modest expansion westward. The regional ecotone between temperate hardwood forests and northern mixed hardwood/conifer forests shifted southwestward by 15–20 km in Minnesota and northwestern Wisconsin. Fraxinus, Ulmus, and other mesic hardwoods expanded in the Big Woods region of southern Minnesota. The increasing density of paleoecological data networks and advances in statistical modeling approaches now enables the confident detection of subtle but significant changes in forest composition over the last 2,000 yr. |
Notaro, Michael; Wang, Fuyao; Yu, Yan: Elucidating observed land surface feedbacks across sub-Saharan Africa. In: Climate Dynamics, vol. 53, no. 3, pp. 1741-1763, 2019, ISSN: 1432-0894. @article{Notaro2019,
title = {Elucidating observed land surface feedbacks across sub-Saharan Africa},
author = {Michael Notaro and Fuyao Wang and Yan Yu},
url = {https://link.springer.com/article/10.1007/s00382-019-04730-3},
doi = {10.1007/s00382-019-04730-3},
issn = {1432-0894},
year = {2019},
date = {2019-08-01},
journal = {Climate Dynamics},
volume = {53},
number = {3},
pages = {1741-1763},
abstract = {This study examines the role of terrestrial forcings on the regional climate of sub-Saharan Africa through the application of a multivariate statistical method, stepwise generalized equilibrium feedback assessment, to an array of observational, reanalysis, and remote sensing data products. By applying multiple datasets, data uncertainty and the robustness of assessed land surface feedbacks are considered. The approach from our 2017 study is expanded to decompose the relative contribution of vegetation, soil moisture, and oceanic forcings; investigate the role of evapotranspiration (ET) partitioning in terrestrial feedbacks; and compare land surface feedbacks among four key regions, namely the Sahel, Greater Horn of Africa, West African monsoon region, and Congo. ET partitioning differs notably among sub-Saharan regions and between available observational datasets. Across sub-Saharan Africa as a whole, oceanic and terrestrial forcings impose a relatively comparable impact on year-round atmospheric conditions. The land surface feedbacks are most pronounced across the semi-arid Sahel and Greater Horn of Africa, although with unique seasonality of such feedbacks between regions. Moisture recycling is the dominant mechanism in these regions, with positive soil moisture--vegetation--rainfall feedbacks. The direct feedback of soil moisture anomalies on atmospheric conditions outweighed that of leaf area index anomalies. There is a clear need for more extensive observations of ET, its partitioning, and soil moisture across sub-Saharan Africa, as these data uncertainties propagate into the reliability of assessed soil moisture--ET feedbacks, particularly across the Sahel.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This study examines the role of terrestrial forcings on the regional climate of sub-Saharan Africa through the application of a multivariate statistical method, stepwise generalized equilibrium feedback assessment, to an array of observational, reanalysis, and remote sensing data products. By applying multiple datasets, data uncertainty and the robustness of assessed land surface feedbacks are considered. The approach from our 2017 study is expanded to decompose the relative contribution of vegetation, soil moisture, and oceanic forcings; investigate the role of evapotranspiration (ET) partitioning in terrestrial feedbacks; and compare land surface feedbacks among four key regions, namely the Sahel, Greater Horn of Africa, West African monsoon region, and Congo. ET partitioning differs notably among sub-Saharan regions and between available observational datasets. Across sub-Saharan Africa as a whole, oceanic and terrestrial forcings impose a relatively comparable impact on year-round atmospheric conditions. The land surface feedbacks are most pronounced across the semi-arid Sahel and Greater Horn of Africa, although with unique seasonality of such feedbacks between regions. Moisture recycling is the dominant mechanism in these regions, with positive soil moisture--vegetation--rainfall feedbacks. The direct feedback of soil moisture anomalies on atmospheric conditions outweighed that of leaf area index anomalies. There is a clear need for more extensive observations of ET, its partitioning, and soil moisture across sub-Saharan Africa, as these data uncertainties propagate into the reliability of assessed soil moisture--ET feedbacks, particularly across the Sahel. |
Loken, Luke C; Crawford, John T; Schramm, Paul J; Stadler, Philipp; Desai, Ankur R; Stanley, Emily H: Large Spatial and Temporal Variability of Carbon Dioxide and Methane in a Eutrophic Lake. In: Journal of Geophysical Research: Biogeosciences, vol. 124, no. 7, pp. 2248-2266, 2019. @article{https://doi.org/10.1029/2019JG005186,
title = {Large Spatial and Temporal Variability of Carbon Dioxide and Methane in a Eutrophic Lake},
author = {Luke C Loken and John T Crawford and Paul J Schramm and Philipp Stadler and Ankur R Desai and Emily H Stanley},
url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2019JG005186},
doi = {https://doi.org/10.1029/2019JG005186},
year = {2019},
date = {2019-07-02},
journal = {Journal of Geophysical Research: Biogeosciences},
volume = {124},
number = {7},
pages = {2248-2266},
abstract = {Abstract Lakes are conduits of greenhouse gases to the atmosphere; however, most efflux estimates for individual lakes are based on extrapolations from a limited number of locations. Within-lake variability in carbon dioxide (CO2) and methane (CH4) arises from differences in water sources, mixing, atmospheric exchange, and biogeochemical transformations, all of which vary across multiple temporal and spatial scales. We asked, how variable are CO2 and CH4 across the surface of a single lake, how do spatial patterns change seasonally, and how well does the typical sampling location represent the entire lake surface? During the 2016 ice-free period, we mapped surface water concentrations of CO2 and CH4 approximately weekly in Lake Mendota (USA) and modeled diffusive gas exchange. During stratification, CO2 was generally lower than atmospheric saturation (mean 19.81 μM) and relatively homogenous (mean coefficient of variation 0.12), whereas CH4 was routinely extremely supersaturated (mean 0.29 μM) with greater spatial heterogeneity (mean coefficient of variation 0.65). During fall mixis, concentrations of both gases increased and became more spatially variable, but their spatial arrangements differed. In this system, samples collected from the lake center reasonably well represented the spatially weighted mean CO2 concentration but overestimated annual CO2 efflux by 21%. For CH4, the lake center underestimated annual diffusive efflux by only 8.6% but poorly represented lakewide concentrations and fluxes on any given day. Upscaling from a single site to the whole lake requires consideration of spatial variation to assess lakewide carbon dynamics due to heterogeneity in within-lake processing, transport to the lake surface, and exchange with the atmosphere.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Abstract Lakes are conduits of greenhouse gases to the atmosphere; however, most efflux estimates for individual lakes are based on extrapolations from a limited number of locations. Within-lake variability in carbon dioxide (CO2) and methane (CH4) arises from differences in water sources, mixing, atmospheric exchange, and biogeochemical transformations, all of which vary across multiple temporal and spatial scales. We asked, how variable are CO2 and CH4 across the surface of a single lake, how do spatial patterns change seasonally, and how well does the typical sampling location represent the entire lake surface? During the 2016 ice-free period, we mapped surface water concentrations of CO2 and CH4 approximately weekly in Lake Mendota (USA) and modeled diffusive gas exchange. During stratification, CO2 was generally lower than atmospheric saturation (mean 19.81 μM) and relatively homogenous (mean coefficient of variation 0.12), whereas CH4 was routinely extremely supersaturated (mean 0.29 μM) with greater spatial heterogeneity (mean coefficient of variation 0.65). During fall mixis, concentrations of both gases increased and became more spatially variable, but their spatial arrangements differed. In this system, samples collected from the lake center reasonably well represented the spatially weighted mean CO2 concentration but overestimated annual CO2 efflux by 21%. For CH4, the lake center underestimated annual diffusive efflux by only 8.6% but poorly represented lakewide concentrations and fluxes on any given day. Upscaling from a single site to the whole lake requires consideration of spatial variation to assess lakewide carbon dynamics due to heterogeneity in within-lake processing, transport to the lake surface, and exchange with the atmosphere. |